Overview

Dataset statistics

Number of variables62
Number of observations99
Missing cells2489
Missing cells (%)40.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory48.1 KiB
Average record size in memory497.3 B

Variable types

Numeric12
Categorical41
Unsupported9

Alerts

type has constant value "regular" Constant
airdate has constant value "2020-12-01" Constant
_embedded.show.externals.tvrage has constant value "19056.0" Constant
_embedded.show.dvdCountry.name has constant value "Japan" Constant
_embedded.show.dvdCountry.code has constant value "JP" Constant
_embedded.show.dvdCountry.timezone has constant value "Asia/Tokyo" Constant
url has a high cardinality: 99 distinct values High cardinality
name has a high cardinality: 93 distinct values High cardinality
_links.self.href has a high cardinality: 99 distinct values High cardinality
_embedded.show.url has a high cardinality: 69 distinct values High cardinality
_embedded.show.name has a high cardinality: 69 distinct values High cardinality
_embedded.show.premiered has a high cardinality: 51 distinct values High cardinality
_embedded.show.officialSite has a high cardinality: 63 distinct values High cardinality
_embedded.show.image.medium has a high cardinality: 66 distinct values High cardinality
_embedded.show.image.original has a high cardinality: 66 distinct values High cardinality
_embedded.show.summary has a high cardinality: 60 distinct values High cardinality
_embedded.show._links.self.href has a high cardinality: 69 distinct values High cardinality
_embedded.show._links.previousepisode.href has a high cardinality: 69 distinct values High cardinality
id is highly correlated with rating.average and 1 other fieldsHigh correlation
season is highly correlated with _embedded.show.id and 2 other fieldsHigh correlation
number is highly correlated with _embedded.show.rating.average and 1 other fieldsHigh correlation
runtime is highly correlated with rating.average and 3 other fieldsHigh correlation
rating.average is highly correlated with id and 8 other fieldsHigh correlation
_embedded.show.id is highly correlated with id and 4 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with runtime and 1 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with runtime and 3 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with season and 9 other fieldsHigh correlation
_embedded.show.weight is highly correlated with rating.average and 1 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with rating.average and 1 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with season and 5 other fieldsHigh correlation
_embedded.show.updated is highly correlated with rating.average and 1 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with _embedded.show.externals.thetvdbHigh correlation
season is highly correlated with _embedded.show.id and 1 other fieldsHigh correlation
number is highly correlated with _embedded.show.rating.averageHigh correlation
runtime is highly correlated with rating.average and 3 other fieldsHigh correlation
rating.average is highly correlated with runtime and 5 other fieldsHigh correlation
_embedded.show.id is highly correlated with season and 2 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with runtime and 1 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with runtime and 3 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with season and 9 other fieldsHigh correlation
_embedded.show.weight is highly correlated with _embedded.show.rating.averageHigh correlation
_embedded.show.webChannel.id is highly correlated with rating.average and 1 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with rating.average and 3 other fieldsHigh correlation
_embedded.show.updated is highly correlated with rating.average and 1 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with _embedded.show.externals.thetvdbHigh correlation
season is highly correlated with _embedded.show.rating.average and 1 other fieldsHigh correlation
number is highly correlated with _embedded.show.rating.averageHigh correlation
runtime is highly correlated with rating.average and 3 other fieldsHigh correlation
rating.average is highly correlated with runtime and 5 other fieldsHigh correlation
_embedded.show.id is highly correlated with _embedded.show.rating.average and 1 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with runtime and 1 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with runtime and 3 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with season and 9 other fieldsHigh correlation
_embedded.show.weight is highly correlated with _embedded.show.rating.averageHigh correlation
_embedded.show.webChannel.id is highly correlated with rating.average and 1 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with season and 3 other fieldsHigh correlation
_embedded.show.updated is highly correlated with rating.average and 1 other fieldsHigh correlation
id is highly correlated with url and 35 other fieldsHigh correlation
url is highly correlated with id and 45 other fieldsHigh correlation
name is highly correlated with id and 35 other fieldsHigh correlation
season is highly correlated with url and 18 other fieldsHigh correlation
number is highly correlated with url and 27 other fieldsHigh correlation
airtime is highly correlated with id and 38 other fieldsHigh correlation
airstamp is highly correlated with id and 40 other fieldsHigh correlation
runtime is highly correlated with id and 36 other fieldsHigh correlation
summary is highly correlated with id and 43 other fieldsHigh correlation
rating.average is highly correlated with url and 25 other fieldsHigh correlation
_links.self.href is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.id is highly correlated with id and 38 other fieldsHigh correlation
_embedded.show.url is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.name is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.type is highly correlated with id and 38 other fieldsHigh correlation
_embedded.show.language is highly correlated with id and 40 other fieldsHigh correlation
_embedded.show.status is highly correlated with id and 34 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with id and 35 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with id and 38 other fieldsHigh correlation
_embedded.show.premiered is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.ended is highly correlated with id and 35 other fieldsHigh correlation
_embedded.show.officialSite is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.schedule.time is highly correlated with id and 39 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with url and 27 other fieldsHigh correlation
_embedded.show.weight is highly correlated with url and 38 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with id and 38 other fieldsHigh correlation
_embedded.show.webChannel.name is highly correlated with id and 43 other fieldsHigh correlation
_embedded.show.webChannel.country.name is highly correlated with id and 38 other fieldsHigh correlation
_embedded.show.webChannel.country.code is highly correlated with id and 38 other fieldsHigh correlation
_embedded.show.webChannel.country.timezone is highly correlated with id and 38 other fieldsHigh correlation
_embedded.show.webChannel.officialSite is highly correlated with id and 36 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with url and 37 other fieldsHigh correlation
_embedded.show.externals.imdb is highly correlated with id and 43 other fieldsHigh correlation
_embedded.show.image.medium is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.image.original is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.summary is highly correlated with id and 44 other fieldsHigh correlation
_embedded.show.updated is highly correlated with id and 39 other fieldsHigh correlation
_embedded.show._links.self.href is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show._links.previousepisode.href is highly correlated with id and 45 other fieldsHigh correlation
image.medium is highly correlated with id and 43 other fieldsHigh correlation
image.original is highly correlated with id and 43 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with url and 24 other fieldsHigh correlation
_embedded.show.network.name is highly correlated with id and 41 other fieldsHigh correlation
_embedded.show.network.country.name is highly correlated with url and 35 other fieldsHigh correlation
_embedded.show.network.country.code is highly correlated with url and 35 other fieldsHigh correlation
_embedded.show.network.country.timezone is highly correlated with url and 35 other fieldsHigh correlation
_embedded.show._links.nextepisode.href is highly correlated with id and 30 other fieldsHigh correlation
runtime has 5 (5.1%) missing values Missing
image has 99 (100.0%) missing values Missing
summary has 79 (79.8%) missing values Missing
rating.average has 96 (97.0%) missing values Missing
_embedded.show.runtime has 29 (29.3%) missing values Missing
_embedded.show.averageRuntime has 3 (3.0%) missing values Missing
_embedded.show.ended has 53 (53.5%) missing values Missing
_embedded.show.officialSite has 8 (8.1%) missing values Missing
_embedded.show.rating.average has 95 (96.0%) missing values Missing
_embedded.show.network has 99 (100.0%) missing values Missing
_embedded.show.webChannel.id has 6 (6.1%) missing values Missing
_embedded.show.webChannel.name has 6 (6.1%) missing values Missing
_embedded.show.webChannel.country.name has 61 (61.6%) missing values Missing
_embedded.show.webChannel.country.code has 61 (61.6%) missing values Missing
_embedded.show.webChannel.country.timezone has 61 (61.6%) missing values Missing
_embedded.show.webChannel.officialSite has 43 (43.4%) missing values Missing
_embedded.show.dvdCountry has 99 (100.0%) missing values Missing
_embedded.show.externals.tvrage has 98 (99.0%) missing values Missing
_embedded.show.externals.thetvdb has 41 (41.4%) missing values Missing
_embedded.show.externals.imdb has 49 (49.5%) missing values Missing
_embedded.show.image.medium has 14 (14.1%) missing values Missing
_embedded.show.image.original has 14 (14.1%) missing values Missing
_embedded.show.summary has 11 (11.1%) missing values Missing
image.medium has 73 (73.7%) missing values Missing
image.original has 73 (73.7%) missing values Missing
_embedded.show.network.id has 86 (86.9%) missing values Missing
_embedded.show.network.name has 86 (86.9%) missing values Missing
_embedded.show.network.country.name has 86 (86.9%) missing values Missing
_embedded.show.network.country.code has 86 (86.9%) missing values Missing
_embedded.show.network.country.timezone has 86 (86.9%) missing values Missing
_embedded.show.network.officialSite has 99 (100.0%) missing values Missing
_embedded.show._links.nextepisode.href has 93 (93.9%) missing values Missing
_embedded.show.webChannel has 99 (100.0%) missing values Missing
_embedded.show.image has 99 (100.0%) missing values Missing
_embedded.show.webChannel.country has 99 (100.0%) missing values Missing
_embedded.show.dvdCountry.name has 98 (99.0%) missing values Missing
_embedded.show.dvdCountry.code has 98 (99.0%) missing values Missing
_embedded.show.dvdCountry.timezone has 98 (99.0%) missing values Missing
url is uniformly distributed Uniform
name is uniformly distributed Uniform
summary is uniformly distributed Uniform
rating.average is uniformly distributed Uniform
_links.self.href is uniformly distributed Uniform
_embedded.show.image.medium is uniformly distributed Uniform
_embedded.show.image.original is uniformly distributed Uniform
image.medium is uniformly distributed Uniform
image.original is uniformly distributed Uniform
_embedded.show.network.name is uniformly distributed Uniform
_embedded.show._links.nextepisode.href is uniformly distributed Uniform
id has unique values Unique
url has unique values Unique
_links.self.href has unique values Unique
image is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.genres is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.schedule.days is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.network is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.dvdCountry is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.network.officialSite is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.webChannel is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.image is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.webChannel.country is an unsupported type, check if it needs cleaning or further analysis Unsupported

Reproduction

Analysis started2022-09-06 02:35:25.782012
Analysis finished2022-09-06 02:35:43.208079
Duration17.43 seconds
Software versionpandas-profiling v3.2.0
Download configurationconfig.json

Variables

id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
UNIQUE

Distinct99
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2021674.182
Minimum1939481
Maximum2379925
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size920.0 B
2022-09-05T21:35:43.286610image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1939481
5-th percentile1964288.9
Q11976152.5
median1978869
Q32033287.5
95-th percentile2290108.2
Maximum2379925
Range440444
Interquartile range (IQR)57135

Descriptive statistics

Standard deviation91562.71371
Coefficient of variation (CV)0.04529053917
Kurtosis5.617572233
Mean2021674.182
Median Absolute Deviation (MAD)9430
Skewness2.467322306
Sum200145744
Variance8383730543
MonotonicityNot monotonic
2022-09-05T21:35:43.402314image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19798241
 
1.0%
20332921
 
1.0%
20332901
 
1.0%
20332891
 
1.0%
20332881
 
1.0%
20332871
 
1.0%
20332861
 
1.0%
20332851
 
1.0%
20332841
 
1.0%
19882991
 
1.0%
Other values (89)89
89.9%
ValueCountFrequency (%)
19394811
1.0%
19568441
1.0%
19600281
1.0%
19604961
1.0%
19639101
1.0%
19643311
1.0%
19645651
1.0%
19685461
1.0%
19685471
1.0%
19692111
1.0%
ValueCountFrequency (%)
23799251
1.0%
23369061
1.0%
23180951
1.0%
23151161
1.0%
23110171
1.0%
22877851
1.0%
22033961
1.0%
21761181
1.0%
21650051
1.0%
21614141
1.0%

url
Categorical

HIGH CARDINALITY
HIGH CORRELATION
UNIFORM
UNIQUE

Distinct99
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size920.0 B
https://www.tvmaze.com/episodes/1979824/sim-for-you-4x16-chanyeols-episode-16
 
1
https://www.tvmaze.com/episodes/2033292/33-rebenka-1x09-9-seria
 
1
https://www.tvmaze.com/episodes/2033290/33-rebenka-1x07-7-seria
 
1
https://www.tvmaze.com/episodes/2033289/33-rebenka-1x06-6-seria
 
1
https://www.tvmaze.com/episodes/2033288/33-rebenka-1x05-5-seria
 
1
Other values (94)
94 

Length

Max length136
Median length96
Mean length76.46464646
Min length58

Characters and Unicode

Total characters7570
Distinct characters39
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique99 ?
Unique (%)100.0%

Sample

1st rowhttps://www.tvmaze.com/episodes/1979824/sim-for-you-4x16-chanyeols-episode-16
2nd rowhttps://www.tvmaze.com/episodes/1979222/kotiki-1x02-seria-2
3rd rowhttps://www.tvmaze.com/episodes/2008027/lab-s-antonom-belaevym-2x06-lolita
4th rowhttps://www.tvmaze.com/episodes/1964565/core-sense-1x09-episode-9
5th rowhttps://www.tvmaze.com/episodes/2052503/wu-shen-zhu-zai-1x80-episode-80

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/episodes/1979824/sim-for-you-4x16-chanyeols-episode-161
 
1.0%
https://www.tvmaze.com/episodes/2033292/33-rebenka-1x09-9-seria1
 
1.0%
https://www.tvmaze.com/episodes/2033290/33-rebenka-1x07-7-seria1
 
1.0%
https://www.tvmaze.com/episodes/2033289/33-rebenka-1x06-6-seria1
 
1.0%
https://www.tvmaze.com/episodes/2033288/33-rebenka-1x05-5-seria1
 
1.0%
https://www.tvmaze.com/episodes/2033287/33-rebenka-1x04-4-seria1
 
1.0%
https://www.tvmaze.com/episodes/2033286/33-rebenka-1x03-3-seria1
 
1.0%
https://www.tvmaze.com/episodes/2033285/33-rebenka-1x02-2-seria1
 
1.0%
https://www.tvmaze.com/episodes/2033284/33-rebenka-1x01-1-seria1
 
1.0%
https://www.tvmaze.com/episodes/1988299/nwa-shockwave-1x01-episode-11
 
1.0%
Other values (89)89
89.9%

Length

2022-09-05T21:35:43.522475image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/episodes/1979824/sim-for-you-4x16-chanyeols-episode-161
 
1.0%
https://www.tvmaze.com/episodes/1975170/the-young-turks-2020-12-01-december-1-20201
 
1.0%
https://www.tvmaze.com/episodes/2008027/lab-s-antonom-belaevym-2x06-lolita1
 
1.0%
https://www.tvmaze.com/episodes/1964565/core-sense-1x09-episode-91
 
1.0%
https://www.tvmaze.com/episodes/2052503/wu-shen-zhu-zai-1x80-episode-801
 
1.0%
https://www.tvmaze.com/episodes/2315116/sono-koi-mousukoshi-atatamemasuka-1x05-episode-51
 
1.0%
https://www.tvmaze.com/episodes/1973538/please-wait-brother-1x17-episode-171
 
1.0%
https://www.tvmaze.com/episodes/1973539/please-wait-brother-1x18-episode-181
 
1.0%
https://www.tvmaze.com/episodes/1984264/fearless-whispers-1x51-episode-511
 
1.0%
https://www.tvmaze.com/episodes/2082171/ling-jian-zun-4x28-di128ji1
 
1.0%
Other values (89)89
89.9%

Most occurring characters

ValueCountFrequency (%)
e633
 
8.4%
-554
 
7.3%
/495
 
6.5%
s493
 
6.5%
t458
 
6.1%
o400
 
5.3%
w332
 
4.4%
a332
 
4.4%
i288
 
3.8%
1276
 
3.6%
Other values (29)3309
43.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter5056
66.8%
Decimal Number1168
 
15.4%
Other Punctuation792
 
10.5%
Dash Punctuation554
 
7.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e633
12.5%
s493
 
9.8%
t458
 
9.1%
o400
 
7.9%
w332
 
6.6%
a332
 
6.6%
i288
 
5.7%
m262
 
5.2%
p256
 
5.1%
d211
 
4.2%
Other values (15)1391
27.5%
Decimal Number
ValueCountFrequency (%)
1276
23.6%
0158
13.5%
2155
13.3%
9127
10.9%
3121
10.4%
788
 
7.5%
882
 
7.0%
659
 
5.1%
451
 
4.4%
551
 
4.4%
Other Punctuation
ValueCountFrequency (%)
/495
62.5%
.198
 
25.0%
:99
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-554
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin5056
66.8%
Common2514
33.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e633
12.5%
s493
 
9.8%
t458
 
9.1%
o400
 
7.9%
w332
 
6.6%
a332
 
6.6%
i288
 
5.7%
m262
 
5.2%
p256
 
5.1%
d211
 
4.2%
Other values (15)1391
27.5%
Common
ValueCountFrequency (%)
-554
22.0%
/495
19.7%
1276
11.0%
.198
 
7.9%
0158
 
6.3%
2155
 
6.2%
9127
 
5.1%
3121
 
4.8%
:99
 
3.9%
788
 
3.5%
Other values (4)243
9.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII7570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e633
 
8.4%
-554
 
7.3%
/495
 
6.5%
s493
 
6.5%
t458
 
6.1%
o400
 
5.3%
w332
 
4.4%
a332
 
4.4%
i288
 
3.8%
1276
 
3.6%
Other values (29)3309
43.7%

name
Categorical

HIGH CARDINALITY
HIGH CORRELATION
UNIFORM

Distinct93
Distinct (%)93.9%
Missing0
Missing (%)0.0%
Memory size920.0 B
Episode 21
 
2
Episode 9
 
2
Episode 17
 
2
Episode 18
 
2
Episode 12
 
2
Other values (88)
89 

Length

Max length61
Median length43
Mean length15.67676768
Min length3

Characters and Unicode

Total characters1552
Distinct characters117
Distinct categories10 ?
Distinct scripts5 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique87 ?
Unique (%)87.9%

Sample

1st rowChanyeol's Episode 16
2nd rowСерия 2
3rd rowЛолита
4th rowEpisode 9
5th rowEpisode 80

Common Values

ValueCountFrequency (%)
Episode 212
 
2.0%
Episode 92
 
2.0%
Episode 172
 
2.0%
Episode 182
 
2.0%
Episode 122
 
2.0%
Episode 12
 
2.0%
1 серия1
 
1.0%
9 серия1
 
1.0%
8 серия1
 
1.0%
7 серия1
 
1.0%
Other values (83)83
83.8%

Length

2022-09-05T21:35:43.634365image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
episode29
 
10.3%
серия14
 
5.0%
6
 
2.1%
the5
 
1.8%
14
 
1.4%
a3
 
1.1%
123
 
1.1%
93
 
1.1%
wedding3
 
1.1%
63
 
1.1%
Other values (191)209
74.1%

Most occurring characters

ValueCountFrequency (%)
183
 
11.8%
e109
 
7.0%
i81
 
5.2%
s76
 
4.9%
o74
 
4.8%
a74
 
4.8%
d59
 
3.8%
n56
 
3.6%
r50
 
3.2%
t46
 
3.0%
Other values (107)744
47.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1017
65.5%
Uppercase Letter198
 
12.8%
Space Separator183
 
11.8%
Decimal Number97
 
6.2%
Other Punctuation35
 
2.3%
Other Letter16
 
1.0%
Close Punctuation2
 
0.1%
Open Punctuation2
 
0.1%
Currency Symbol1
 
0.1%
Dash Punctuation1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e109
 
10.7%
i81
 
8.0%
s76
 
7.5%
o74
 
7.3%
a74
 
7.3%
d59
 
5.8%
n56
 
5.5%
r50
 
4.9%
t46
 
4.5%
p41
 
4.0%
Other values (39)351
34.5%
Uppercase Letter
ValueCountFrequency (%)
E42
21.2%
S19
 
9.6%
C13
 
6.6%
B13
 
6.6%
A13
 
6.6%
H9
 
4.5%
T8
 
4.0%
K7
 
3.5%
D7
 
3.5%
N7
 
3.5%
Other values (22)60
30.3%
Other Letter
ValueCountFrequency (%)
و3
18.8%
ا2
12.5%
1
 
6.2%
1
 
6.2%
ه1
 
6.2%
ل1
 
6.2%
ر1
 
6.2%
گ1
 
6.2%
ب1
 
6.2%
ز1
 
6.2%
Other values (3)3
18.8%
Decimal Number
ValueCountFrequency (%)
128
28.9%
216
16.5%
89
 
9.3%
68
 
8.2%
08
 
8.2%
47
 
7.2%
37
 
7.2%
96
 
6.2%
55
 
5.2%
73
 
3.1%
Other Punctuation
ValueCountFrequency (%)
'9
25.7%
.8
22.9%
&5
14.3%
,4
11.4%
?3
 
8.6%
!3
 
8.6%
"2
 
5.7%
:1
 
2.9%
Space Separator
ValueCountFrequency (%)
183
100.0%
Close Punctuation
ValueCountFrequency (%)
)2
100.0%
Open Punctuation
ValueCountFrequency (%)
(2
100.0%
Currency Symbol
ValueCountFrequency (%)
£1
100.0%
Dash Punctuation
ValueCountFrequency (%)
-1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1046
67.4%
Common321
 
20.7%
Cyrillic169
 
10.9%
Arabic14
 
0.9%
Han2
 
0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e109
 
10.4%
i81
 
7.7%
s76
 
7.3%
o74
 
7.1%
a74
 
7.1%
d59
 
5.6%
n56
 
5.4%
r50
 
4.8%
t46
 
4.4%
E42
 
4.0%
Other values (39)379
36.2%
Cyrillic
ValueCountFrequency (%)
р20
11.8%
с19
11.2%
и19
11.2%
е18
10.7%
а17
10.1%
я14
 
8.3%
о9
 
5.3%
т6
 
3.6%
м6
 
3.6%
н5
 
3.0%
Other values (22)36
21.3%
Common
ValueCountFrequency (%)
183
57.0%
128
 
8.7%
216
 
5.0%
89
 
2.8%
'9
 
2.8%
68
 
2.5%
.8
 
2.5%
08
 
2.5%
47
 
2.2%
37
 
2.2%
Other values (13)38
 
11.8%
Arabic
ValueCountFrequency (%)
و3
21.4%
ا2
14.3%
ه1
 
7.1%
ل1
 
7.1%
ر1
 
7.1%
گ1
 
7.1%
ب1
 
7.1%
ز1
 
7.1%
ی1
 
7.1%
س1
 
7.1%
Han
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1361
87.7%
Cyrillic169
 
10.9%
Arabic14
 
0.9%
None6
 
0.4%
CJK2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
183
 
13.4%
e109
 
8.0%
i81
 
6.0%
s76
 
5.6%
o74
 
5.4%
a74
 
5.4%
d59
 
4.3%
n56
 
4.1%
r50
 
3.7%
t46
 
3.4%
Other values (58)553
40.6%
Cyrillic
ValueCountFrequency (%)
р20
11.8%
с19
11.2%
и19
11.2%
е18
10.7%
а17
10.1%
я14
 
8.3%
о9
 
5.3%
т6
 
3.6%
м6
 
3.6%
н5
 
3.0%
Other values (22)36
21.3%
Arabic
ValueCountFrequency (%)
و3
21.4%
ا2
14.3%
ه1
 
7.1%
ل1
 
7.1%
ر1
 
7.1%
گ1
 
7.1%
ب1
 
7.1%
ز1
 
7.1%
ی1
 
7.1%
س1
 
7.1%
None
ValueCountFrequency (%)
ü2
33.3%
ö2
33.3%
á1
16.7%
£1
16.7%
CJK
ValueCountFrequency (%)
1
50.0%
1
50.0%

season
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct10
Distinct (%)10.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean205.989899
Minimum1
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size920.0 B
2022-09-05T21:35:43.718642image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile2020
Maximum2020
Range2019
Interquartile range (IQR)1

Descriptive statistics

Standard deviation611.1634688
Coefficient of variation (CV)2.966958437
Kurtosis5.33757248
Mean205.989899
Median Absolute Deviation (MAD)0
Skewness2.688813235
Sum20393
Variance373520.7856
MonotonicityNot monotonic
2022-09-05T21:35:43.801554image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
171
71.7%
202010
 
10.1%
44
 
4.0%
24
 
4.0%
33
 
3.0%
72
 
2.0%
82
 
2.0%
101
 
1.0%
181
 
1.0%
311
 
1.0%
ValueCountFrequency (%)
171
71.7%
24
 
4.0%
33
 
3.0%
44
 
4.0%
72
 
2.0%
82
 
2.0%
101
 
1.0%
181
 
1.0%
311
 
1.0%
202010
 
10.1%
ValueCountFrequency (%)
202010
 
10.1%
311
 
1.0%
181
 
1.0%
101
 
1.0%
82
 
2.0%
72
 
2.0%
44
 
4.0%
33
 
3.0%
24
 
4.0%
171
71.7%

number
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct42
Distinct (%)42.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.83838384
Minimum1
Maximum328
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size920.0 B
2022-09-05T21:35:43.893570image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14.5
median11
Q322
95-th percentile93.4
Maximum328
Range327
Interquartile range (IQR)17.5

Descriptive statistics

Standard deviation47.86646115
Coefficient of variation (CV)1.852533094
Kurtosis24.34280918
Mean25.83838384
Median Absolute Deviation (MAD)8
Skewness4.557126152
Sum2558
Variance2291.198103
MonotonicityNot monotonic
2022-09-05T21:35:43.999594image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
38
 
8.1%
17
 
7.1%
26
 
6.1%
95
 
5.1%
44
 
4.0%
74
 
4.0%
84
 
4.0%
114
 
4.0%
124
 
4.0%
64
 
4.0%
Other values (32)49
49.5%
ValueCountFrequency (%)
17
7.1%
26
6.1%
38
8.1%
44
4.0%
53
 
3.0%
64
4.0%
74
4.0%
84
4.0%
95
5.1%
102
 
2.0%
ValueCountFrequency (%)
3281
1.0%
2871
1.0%
1411
1.0%
1051
1.0%
971
1.0%
931
1.0%
801
1.0%
721
1.0%
561
1.0%
541
1.0%

type
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size920.0 B
regular
99 

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters693
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowregular
2nd rowregular
3rd rowregular
4th rowregular
5th rowregular

Common Values

ValueCountFrequency (%)
regular99
100.0%

Length

2022-09-05T21:35:44.086186image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:35:44.165210image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
regular99
100.0%

Most occurring characters

ValueCountFrequency (%)
r198
28.6%
e99
14.3%
g99
14.3%
u99
14.3%
l99
14.3%
a99
14.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter693
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r198
28.6%
e99
14.3%
g99
14.3%
u99
14.3%
l99
14.3%
a99
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin693
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
r198
28.6%
e99
14.3%
g99
14.3%
u99
14.3%
l99
14.3%
a99
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII693
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r198
28.6%
e99
14.3%
g99
14.3%
u99
14.3%
l99
14.3%
a99
14.3%

airdate
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size920.0 B
2020-12-01
99 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters990
Distinct characters4
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-12-01
2nd row2020-12-01
3rd row2020-12-01
4th row2020-12-01
5th row2020-12-01

Common Values

ValueCountFrequency (%)
2020-12-0199
100.0%

Length

2022-09-05T21:35:44.229346image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:35:44.302551image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
2020-12-0199
100.0%

Most occurring characters

ValueCountFrequency (%)
2297
30.0%
0297
30.0%
-198
20.0%
1198
20.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number792
80.0%
Dash Punctuation198
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2297
37.5%
0297
37.5%
1198
25.0%
Dash Punctuation
ValueCountFrequency (%)
-198
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common990
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2297
30.0%
0297
30.0%
-198
20.0%
1198
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII990
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2297
30.0%
0297
30.0%
-198
20.0%
1198
20.0%

airtime
Categorical

HIGH CORRELATION

Distinct15
Distinct (%)15.2%
Missing0
Missing (%)0.0%
Memory size920.0 B
65 
20:00
13 
06:00
 
6
10:00
 
2
12:00
 
2
Other values (10)
11 

Length

Max length5
Median length0
Mean length1.717171717
Min length0

Characters and Unicode

Total characters170
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)9.1%

Sample

1st row06:00
2nd row
3rd row
4th row10:00
5th row10:00

Common Values

ValueCountFrequency (%)
65
65.7%
20:0013
 
13.1%
06:006
 
6.1%
10:002
 
2.0%
12:002
 
2.0%
20:402
 
2.0%
08:001
 
1.0%
17:001
 
1.0%
17:351
 
1.0%
00:001
 
1.0%
Other values (5)5
 
5.1%

Length

2022-09-05T21:35:44.369640image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
20:0013
38.2%
06:006
17.6%
10:002
 
5.9%
12:002
 
5.9%
20:402
 
5.9%
08:001
 
2.9%
17:001
 
2.9%
17:351
 
2.9%
00:001
 
2.9%
07:001
 
2.9%
Other values (4)4
 
11.8%

Most occurring characters

ValueCountFrequency (%)
091
53.5%
:34
 
20.0%
220
 
11.8%
17
 
4.1%
66
 
3.5%
73
 
1.8%
53
 
1.8%
42
 
1.2%
82
 
1.2%
32
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number136
80.0%
Other Punctuation34
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
091
66.9%
220
 
14.7%
17
 
5.1%
66
 
4.4%
73
 
2.2%
53
 
2.2%
42
 
1.5%
82
 
1.5%
32
 
1.5%
Other Punctuation
ValueCountFrequency (%)
:34
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common170
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
091
53.5%
:34
 
20.0%
220
 
11.8%
17
 
4.1%
66
 
3.5%
73
 
1.8%
53
 
1.8%
42
 
1.2%
82
 
1.2%
32
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII170
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
091
53.5%
:34
 
20.0%
220
 
11.8%
17
 
4.1%
66
 
3.5%
73
 
1.8%
53
 
1.8%
42
 
1.2%
82
 
1.2%
32
 
1.2%

airstamp
Categorical

HIGH CORRELATION

Distinct20
Distinct (%)20.2%
Missing0
Missing (%)0.0%
Memory size920.0 B
2020-12-01T12:00:00+00:00
65 
2020-12-01T05:00:00+00:00
 
5
2020-12-01T04:00:00+00:00
 
4
2020-12-01T17:00:00+00:00
 
4
2020-12-01T09:00:00+00:00
 
2
Other values (15)
19 

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters2475
Distinct characters13
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)11.1%

Sample

1st row2020-11-30T21:00:00+00:00
2nd row2020-12-01T00:00:00+00:00
3rd row2020-12-01T00:00:00+00:00
4th row2020-12-01T02:00:00+00:00
5th row2020-12-01T02:00:00+00:00

Common Values

ValueCountFrequency (%)
2020-12-01T12:00:00+00:0065
65.7%
2020-12-01T05:00:00+00:005
 
5.1%
2020-12-01T04:00:00+00:004
 
4.0%
2020-12-01T17:00:00+00:004
 
4.0%
2020-12-01T09:00:00+00:002
 
2.0%
2020-12-01T02:00:00+00:002
 
2.0%
2020-12-01T19:40:00+00:002
 
2.0%
2020-12-01T00:00:00+00:002
 
2.0%
2020-12-01T11:00:00+00:002
 
2.0%
2020-12-01T13:00:00+00:001
 
1.0%
Other values (10)10
 
10.1%

Length

2022-09-05T21:35:44.456523image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-01t12:00:00+00:0065
65.7%
2020-12-01t05:00:00+00:005
 
5.1%
2020-12-01t04:00:00+00:004
 
4.0%
2020-12-01t17:00:00+00:004
 
4.0%
2020-12-01t09:00:00+00:002
 
2.0%
2020-12-01t02:00:00+00:002
 
2.0%
2020-12-01t19:40:00+00:002
 
2.0%
2020-12-01t00:00:00+00:002
 
2.0%
2020-12-01t11:00:00+00:002
 
2.0%
2020-12-01t07:00:00+00:001
 
1.0%
Other values (10)10
 
10.1%

Most occurring characters

ValueCountFrequency (%)
01104
44.6%
2366
 
14.8%
:297
 
12.0%
1278
 
11.2%
-198
 
8.0%
T99
 
4.0%
+99
 
4.0%
59
 
0.4%
47
 
0.3%
37
 
0.3%
Other values (3)11
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number1782
72.0%
Other Punctuation297
 
12.0%
Dash Punctuation198
 
8.0%
Uppercase Letter99
 
4.0%
Math Symbol99
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
01104
62.0%
2366
 
20.5%
1278
 
15.6%
59
 
0.5%
47
 
0.4%
37
 
0.4%
75
 
0.3%
95
 
0.3%
61
 
0.1%
Other Punctuation
ValueCountFrequency (%)
:297
100.0%
Dash Punctuation
ValueCountFrequency (%)
-198
100.0%
Uppercase Letter
ValueCountFrequency (%)
T99
100.0%
Math Symbol
ValueCountFrequency (%)
+99
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common2376
96.0%
Latin99
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
01104
46.5%
2366
 
15.4%
:297
 
12.5%
1278
 
11.7%
-198
 
8.3%
+99
 
4.2%
59
 
0.4%
47
 
0.3%
37
 
0.3%
75
 
0.2%
Other values (2)6
 
0.3%
Latin
ValueCountFrequency (%)
T99
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII2475
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
01104
44.6%
2366
 
14.8%
:297
 
12.0%
1278
 
11.2%
-198
 
8.0%
T99
 
4.0%
+99
 
4.0%
59
 
0.4%
47
 
0.3%
37
 
0.3%
Other values (3)11
 
0.4%

runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct35
Distinct (%)37.2%
Missing5
Missing (%)5.1%
Infinite0
Infinite (%)0.0%
Mean31.90425532
Minimum5
Maximum120
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size920.0 B
2022-09-05T21:35:44.558775image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile7.65
Q113
median25.5
Q345
95-th percentile70.5
Maximum120
Range115
Interquartile range (IQR)32

Descriptive statistics

Standard deviation22.93800394
Coefficient of variation (CV)0.718963778
Kurtosis3.853529504
Mean31.90425532
Median Absolute Deviation (MAD)13.5
Skewness1.67667983
Sum2999
Variance526.1520247
MonotonicityNot monotonic
2022-09-05T21:35:44.663446image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
4516
16.2%
1311
 
11.1%
126
 
6.1%
144
 
4.0%
234
 
4.0%
304
 
4.0%
153
 
3.0%
373
 
3.0%
603
 
3.0%
253
 
3.0%
Other values (25)37
37.4%
(Missing)5
 
5.1%
ValueCountFrequency (%)
53
 
3.0%
61
 
1.0%
71
 
1.0%
81
 
1.0%
91
 
1.0%
101
 
1.0%
126
6.1%
1311
11.1%
144
 
4.0%
153
 
3.0%
ValueCountFrequency (%)
1202
 
2.0%
941
 
1.0%
902
 
2.0%
603
 
3.0%
571
 
1.0%
511
 
1.0%
503
 
3.0%
4516
16.2%
441
 
1.0%
411
 
1.0%

image
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing99
Missing (%)100.0%
Memory size920.0 B

summary
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct20
Distinct (%)100.0%
Missing79
Missing (%)79.8%
Memory size920.0 B
<p><b>#ObtainedAConversationalSkill #WeSetUpATent♥ #ManySmiles</b></p>
 
1
<p>Amie and Caolan had different ideas for their big day. She wanted a small wedding abroad, but he persuaded her to have a large and extravagant celebration.</p>
 
1
<p>Cheyenne se fait passer pour le bras droit de l'Anglais auprès d'un passeur nigérian.</p>
 
1
<p>Cheyenne découvre qu'un policier ripou dont elle ignore l'identité est l'informateur de Yannick.</p>
 
1
<p>K2 is a mysterious and extremly destructive drug that 18 yr old Yazz not only abused but also trafficked, earning him 100k a week while also causing him to spiral out of control.</p>
 
1
Other values (15)
15 

Length

Max length1077
Median length160
Mean length208.95
Min length60

Characters and Unicode

Total characters4179
Distinct characters79
Distinct categories11 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)100.0%

Sample

1st row<p><b>#ObtainedAConversationalSkill #WeSetUpATent♥ #ManySmiles</b></p>
2nd row<p>This Giving Tuesday, the crew heads to Mike's hometown of Baltimore, MD to give back to Dawod Thomas. Honoring the legacy of his dad, Dawod created My Fathers Plan, a youth-focused community cleanup program dedicated to cultivating change in the inner-city through community activism, tutoring and mentoring.</p>
3rd row<p>Timothy Omundson (Psych) joins me this week and pours it all out about his heartbreaking experience with the freak accident stroke he suffered during the zenith of his career and the best shape of his life.</p>
4th row<p>Genetically-engineered corn, corn silage, and sweet corn.</p>
5th row<p>Jen practices magical spells with Vee.  When Jen, Vee, Dong, and Jay fall asleep watching a movie, Vee has no choice but to sleep over at Jen's house.  </p>

Common Values

ValueCountFrequency (%)
<p><b>#ObtainedAConversationalSkill #WeSetUpATent♥ #ManySmiles</b></p>1
 
1.0%
<p>Amie and Caolan had different ideas for their big day. She wanted a small wedding abroad, but he persuaded her to have a large and extravagant celebration.</p>1
 
1.0%
<p>Cheyenne se fait passer pour le bras droit de l'Anglais auprès d'un passeur nigérian.</p>1
 
1.0%
<p>Cheyenne découvre qu'un policier ripou dont elle ignore l'identité est l'informateur de Yannick.</p>1
 
1.0%
<p>K2 is a mysterious and extremly destructive drug that 18 yr old Yazz not only abused but also trafficked, earning him 100k a week while also causing him to spiral out of control.</p>1
 
1.0%
<p>Inside The Hill breaks down Trump's voter fraud conspiracy theories, Biden's cabinet picks, and Senate candidate Kelly Loeffler's campaign ad with guest Rep. Linda Sanchez (D-CA).</p>1
 
1.0%
<p>As Claire's world begins to crumble, an uncertain Eric is pressed to reveal intimate details of his relationship.</p>1
 
1.0%
<p>After the audition, 'Yuki Ebana' was confessed to 'Seiichi Izumi'. 'Shiori Kato' and 'Hitoko Murakami' witnessed it, and Hitoko, who had been thinking about Seiichi, screamed and ran away, and Shiori chased it.<br />On the other hand, for some reason, 'Ryo' will be drunk with Seiichi's band members 'Taki Hiroto' and 'Tsubaki Aoi', and will be re-drinked at Taki and Taki's house. Taki tells Ryo that he is thinking of leaving the band and becoming a doctor. Ryo presses the taiko stamp that Taki can be compatible, but Taki is not serious. Taki notices that something is wrong with Ryo's body, but Ryo tells others to keep silent.<br />In Seiichi's confession, Yuki and Hitoko were jerky. Meanwhile, the president 'Yuichi Yanagishita' called and told that the major debut of 'Chahhan' was decided. Three people who rejoice.<br />However, when I went to the office a few days later, I found that the debut song was not the original song, but a song made by a stranger ('77'). The three are not convinced, but Yuki remembers something stuck in the lyrics of 'No. 77' ...</p>1
 
1.0%
<p>Kiki is flustered to learn that Takumi in fact heard her confess her feelings, and now he has something he really wants to tell her. Meanwhile at work, the new "mobile convenience store" project is launched. When Kiki sees Takumi and Riho together, however, she decides it's best to forget about him. But Makoto's own feelings for her haven't changed, and he decides it's time to take their relationship to the next level.</p>1
 
1.0%
<p>Hannah and Olly decided to plan their wedding themselves. Did they make the right decision, or would they hire a planner if they had their time again?</p>1
 
1.0%
Other values (10)10
 
10.1%
(Missing)79
79.8%

Length

2022-09-05T21:35:44.760289image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the28
 
4.2%
and27
 
4.0%
to21
 
3.1%
a14
 
2.1%
of11
 
1.6%
but10
 
1.5%
that8
 
1.2%
their8
 
1.2%
is8
 
1.2%
with7
 
1.0%
Other values (404)530
78.9%

Most occurring characters

ValueCountFrequency (%)
651
15.6%
e378
 
9.0%
i265
 
6.3%
t257
 
6.1%
a252
 
6.0%
n223
 
5.3%
o214
 
5.1%
s183
 
4.4%
r172
 
4.1%
h166
 
4.0%
Other values (69)1418
33.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3095
74.1%
Space Separator654
 
15.6%
Other Punctuation165
 
3.9%
Uppercase Letter132
 
3.2%
Math Symbol90
 
2.2%
Decimal Number25
 
0.6%
Dash Punctuation8
 
0.2%
Close Punctuation3
 
0.1%
Currency Symbol3
 
0.1%
Open Punctuation3
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e378
12.2%
i265
 
8.6%
t257
 
8.3%
a252
 
8.1%
n223
 
7.2%
o214
 
6.9%
s183
 
5.9%
r172
 
5.6%
h166
 
5.4%
d149
 
4.8%
Other values (18)836
27.0%
Uppercase Letter
ValueCountFrequency (%)
T20
15.2%
S13
 
9.8%
A10
 
7.6%
C9
 
6.8%
D8
 
6.1%
H8
 
6.1%
M8
 
6.1%
R7
 
5.3%
Y7
 
5.3%
I6
 
4.5%
Other values (13)36
27.3%
Other Punctuation
ValueCountFrequency (%)
,48
29.1%
'44
26.7%
.39
23.6%
/24
14.5%
#3
 
1.8%
?2
 
1.2%
"2
 
1.2%
!1
 
0.6%
;1
 
0.6%
&1
 
0.6%
Decimal Number
ValueCountFrequency (%)
012
48.0%
74
 
16.0%
13
 
12.0%
62
 
8.0%
31
 
4.0%
51
 
4.0%
81
 
4.0%
21
 
4.0%
Space Separator
ValueCountFrequency (%)
651
99.5%
 3
 
0.5%
Math Symbol
ValueCountFrequency (%)
>45
50.0%
<45
50.0%
Dash Punctuation
ValueCountFrequency (%)
-6
75.0%
2
 
25.0%
Close Punctuation
ValueCountFrequency (%)
)3
100.0%
Currency Symbol
ValueCountFrequency (%)
£3
100.0%
Open Punctuation
ValueCountFrequency (%)
(3
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3227
77.2%
Common952
 
22.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e378
 
11.7%
i265
 
8.2%
t257
 
8.0%
a252
 
7.8%
n223
 
6.9%
o214
 
6.6%
s183
 
5.7%
r172
 
5.3%
h166
 
5.1%
d149
 
4.6%
Other values (41)968
30.0%
Common
ValueCountFrequency (%)
651
68.4%
,48
 
5.0%
>45
 
4.7%
<45
 
4.7%
'44
 
4.6%
.39
 
4.1%
/24
 
2.5%
012
 
1.3%
-6
 
0.6%
74
 
0.4%
Other values (18)34
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII4166
99.7%
None10
 
0.2%
Punctuation2
 
< 0.1%
Misc Symbols1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
651
15.6%
e378
 
9.1%
i265
 
6.4%
t257
 
6.2%
a252
 
6.0%
n223
 
5.4%
o214
 
5.1%
s183
 
4.4%
r172
 
4.1%
h166
 
4.0%
Other values (63)1405
33.7%
None
ValueCountFrequency (%)
£3
30.0%
é3
30.0%
 3
30.0%
è1
 
10.0%
Punctuation
ValueCountFrequency (%)
2
100.0%
Misc Symbols
ValueCountFrequency (%)
1
100.0%

rating.average
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct3
Distinct (%)100.0%
Missing96
Missing (%)97.0%
Memory size920.0 B
8.0
7.5
7.7

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters9
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st row8.0
2nd row7.5
3rd row7.7

Common Values

ValueCountFrequency (%)
8.01
 
1.0%
7.51
 
1.0%
7.71
 
1.0%
(Missing)96
97.0%

Length

2022-09-05T21:35:44.843878image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:35:44.923346image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
8.01
33.3%
7.51
33.3%
7.71
33.3%

Most occurring characters

ValueCountFrequency (%)
.3
33.3%
73
33.3%
81
 
11.1%
01
 
11.1%
51
 
11.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number6
66.7%
Other Punctuation3
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
73
50.0%
81
 
16.7%
01
 
16.7%
51
 
16.7%
Other Punctuation
ValueCountFrequency (%)
.3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common9
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
.3
33.3%
73
33.3%
81
 
11.1%
01
 
11.1%
51
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII9
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
.3
33.3%
73
33.3%
81
 
11.1%
01
 
11.1%
51
 
11.1%

_links.self.href
Categorical

HIGH CARDINALITY
HIGH CORRELATION
UNIFORM
UNIQUE

Distinct99
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size920.0 B
https://api.tvmaze.com/episodes/1979824
 
1
https://api.tvmaze.com/episodes/2033292
 
1
https://api.tvmaze.com/episodes/2033290
 
1
https://api.tvmaze.com/episodes/2033289
 
1
https://api.tvmaze.com/episodes/2033288
 
1
Other values (94)
94 

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters3861
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique99 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/1979824
2nd rowhttps://api.tvmaze.com/episodes/1979222
3rd rowhttps://api.tvmaze.com/episodes/2008027
4th rowhttps://api.tvmaze.com/episodes/1964565
5th rowhttps://api.tvmaze.com/episodes/2052503

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19798241
 
1.0%
https://api.tvmaze.com/episodes/20332921
 
1.0%
https://api.tvmaze.com/episodes/20332901
 
1.0%
https://api.tvmaze.com/episodes/20332891
 
1.0%
https://api.tvmaze.com/episodes/20332881
 
1.0%
https://api.tvmaze.com/episodes/20332871
 
1.0%
https://api.tvmaze.com/episodes/20332861
 
1.0%
https://api.tvmaze.com/episodes/20332851
 
1.0%
https://api.tvmaze.com/episodes/20332841
 
1.0%
https://api.tvmaze.com/episodes/19882991
 
1.0%
Other values (89)89
89.9%

Length

2022-09-05T21:35:44.993531image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19798241
 
1.0%
https://api.tvmaze.com/episodes/19751701
 
1.0%
https://api.tvmaze.com/episodes/20080271
 
1.0%
https://api.tvmaze.com/episodes/19645651
 
1.0%
https://api.tvmaze.com/episodes/20525031
 
1.0%
https://api.tvmaze.com/episodes/23151161
 
1.0%
https://api.tvmaze.com/episodes/19735381
 
1.0%
https://api.tvmaze.com/episodes/19735391
 
1.0%
https://api.tvmaze.com/episodes/19842641
 
1.0%
https://api.tvmaze.com/episodes/20821711
 
1.0%
Other values (89)89
89.9%

Most occurring characters

ValueCountFrequency (%)
/396
 
10.3%
p297
 
7.7%
s297
 
7.7%
e297
 
7.7%
t297
 
7.7%
o198
 
5.1%
a198
 
5.1%
i198
 
5.1%
.198
 
5.1%
m198
 
5.1%
Other values (16)1287
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2475
64.1%
Other Punctuation693
 
17.9%
Decimal Number693
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p297
12.0%
s297
12.0%
e297
12.0%
t297
12.0%
o198
8.0%
a198
8.0%
i198
8.0%
m198
8.0%
h99
 
4.0%
d99
 
4.0%
Other values (3)297
12.0%
Decimal Number
ValueCountFrequency (%)
1115
16.6%
9112
16.2%
284
12.1%
774
10.7%
373
10.5%
066
9.5%
860
8.7%
644
 
6.3%
537
 
5.3%
428
 
4.0%
Other Punctuation
ValueCountFrequency (%)
/396
57.1%
.198
28.6%
:99
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin2475
64.1%
Common1386
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/396
28.6%
.198
14.3%
1115
 
8.3%
9112
 
8.1%
:99
 
7.1%
284
 
6.1%
774
 
5.3%
373
 
5.3%
066
 
4.8%
860
 
4.3%
Other values (3)109
 
7.9%
Latin
ValueCountFrequency (%)
p297
12.0%
s297
12.0%
e297
12.0%
t297
12.0%
o198
8.0%
a198
8.0%
i198
8.0%
m198
8.0%
h99
 
4.0%
d99
 
4.0%
Other values (3)297
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII3861
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/396
 
10.3%
p297
 
7.7%
s297
 
7.7%
e297
 
7.7%
t297
 
7.7%
o198
 
5.1%
a198
 
5.1%
i198
 
5.1%
.198
 
5.1%
m198
 
5.1%
Other values (16)1287
33.3%

_embedded.show.id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct69
Distinct (%)69.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47907.59596
Minimum2504
Maximum63719
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size920.0 B
2022-09-05T21:35:45.377038image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum2504
5-th percentile17394.7
Q146419.5
median52073
Q353282
95-th percentile58812.2
Maximum63719
Range61215
Interquartile range (IQR)6862.5

Descriptive statistics

Standard deviation11519.29102
Coefficient of variation (CV)0.2404481125
Kurtosis5.043491417
Mean47907.59596
Median Absolute Deviation (MAD)1412
Skewness-2.246298578
Sum4742852
Variance132694065.7
MonotonicityNot monotonic
2022-09-05T21:35:45.486872image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5328212
 
12.1%
453896
 
6.1%
553644
 
4.0%
518933
 
3.0%
521072
 
2.0%
521592
 
2.0%
501062
 
2.0%
518702
 
2.0%
521642
 
2.0%
520382
 
2.0%
Other values (59)62
62.6%
ValueCountFrequency (%)
25041
1.0%
64411
1.0%
133811
1.0%
133921
1.0%
152501
1.0%
176331
1.0%
214911
1.0%
262681
1.0%
306061
1.0%
320871
1.0%
ValueCountFrequency (%)
637191
 
1.0%
617551
 
1.0%
616741
 
1.0%
615301
 
1.0%
607851
 
1.0%
585931
 
1.0%
573391
 
1.0%
553644
4.0%
550161
 
1.0%
541121
 
1.0%

_embedded.show.url
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct69
Distinct (%)69.7%
Missing0
Missing (%)0.0%
Memory size920.0 B
https://www.tvmaze.com/shows/53282/33-rebenka
12 
https://www.tvmaze.com/shows/45389/obsolete
 
6
https://www.tvmaze.com/shows/55364/countdown-to-i-do
 
4
https://www.tvmaze.com/shows/51893/exit-nordpolen
 
3
https://www.tvmaze.com/shows/52107/new-face
 
2
Other values (64)
72 

Length

Max length71
Median length58
Mean length49.55555556
Min length40

Characters and Unicode

Total characters4906
Distinct characters39
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique56 ?
Unique (%)56.6%

Sample

1st rowhttps://www.tvmaze.com/shows/41648/sim-for-you
2nd rowhttps://www.tvmaze.com/shows/52198/kotiki
3rd rowhttps://www.tvmaze.com/shows/52933/lab-s-antonom-belaevym
4th rowhttps://www.tvmaze.com/shows/51336/core-sense
5th rowhttps://www.tvmaze.com/shows/54033/wu-shen-zhu-zai

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/shows/53282/33-rebenka12
 
12.1%
https://www.tvmaze.com/shows/45389/obsolete6
 
6.1%
https://www.tvmaze.com/shows/55364/countdown-to-i-do4
 
4.0%
https://www.tvmaze.com/shows/51893/exit-nordpolen3
 
3.0%
https://www.tvmaze.com/shows/52107/new-face2
 
2.0%
https://www.tvmaze.com/shows/52159/to-love2
 
2.0%
https://www.tvmaze.com/shows/50106/cheyenne-et-lola2
 
2.0%
https://www.tvmaze.com/shows/51870/something-just-like-this2
 
2.0%
https://www.tvmaze.com/shows/52164/the-holiday-movies-that-made-us2
 
2.0%
https://www.tvmaze.com/shows/52038/please-wait-brother2
 
2.0%
Other values (59)62
62.6%

Length

2022-09-05T21:35:45.595108image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/shows/53282/33-rebenka12
 
12.1%
https://www.tvmaze.com/shows/45389/obsolete6
 
6.1%
https://www.tvmaze.com/shows/55364/countdown-to-i-do4
 
4.0%
https://www.tvmaze.com/shows/51893/exit-nordpolen3
 
3.0%
https://www.tvmaze.com/shows/52164/the-holiday-movies-that-made-us2
 
2.0%
https://www.tvmaze.com/shows/52106/insect-detective2
 
2.0%
https://www.tvmaze.com/shows/52104/twisted-fate-of-love2
 
2.0%
https://www.tvmaze.com/shows/52038/please-wait-brother2
 
2.0%
https://www.tvmaze.com/shows/52108/psych-hunter2
 
2.0%
https://www.tvmaze.com/shows/51870/something-just-like-this2
 
2.0%
Other values (59)62
62.6%

Most occurring characters

ValueCountFrequency (%)
/495
 
10.1%
w419
 
8.5%
t398
 
8.1%
s375
 
7.6%
o309
 
6.3%
e265
 
5.4%
h242
 
4.9%
m230
 
4.7%
a211
 
4.3%
.198
 
4.0%
Other values (29)1764
36.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3437
70.1%
Other Punctuation792
 
16.1%
Decimal Number519
 
10.6%
Dash Punctuation158
 
3.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w419
12.2%
t398
11.6%
s375
10.9%
o309
9.0%
e265
 
7.7%
h242
 
7.0%
m230
 
6.7%
a211
 
6.1%
c129
 
3.8%
v120
 
3.5%
Other values (15)739
21.5%
Decimal Number
ValueCountFrequency (%)
589
17.1%
389
17.1%
267
12.9%
163
12.1%
445
8.7%
844
8.5%
038
7.3%
636
6.9%
928
 
5.4%
720
 
3.9%
Other Punctuation
ValueCountFrequency (%)
/495
62.5%
.198
 
25.0%
:99
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-158
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3437
70.1%
Common1469
29.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
w419
12.2%
t398
11.6%
s375
10.9%
o309
9.0%
e265
 
7.7%
h242
 
7.0%
m230
 
6.7%
a211
 
6.1%
c129
 
3.8%
v120
 
3.5%
Other values (15)739
21.5%
Common
ValueCountFrequency (%)
/495
33.7%
.198
 
13.5%
-158
 
10.8%
:99
 
6.7%
589
 
6.1%
389
 
6.1%
267
 
4.6%
163
 
4.3%
445
 
3.1%
844
 
3.0%
Other values (4)122
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII4906
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/495
 
10.1%
w419
 
8.5%
t398
 
8.1%
s375
 
7.6%
o309
 
6.3%
e265
 
5.4%
h242
 
4.9%
m230
 
4.7%
a211
 
4.3%
.198
 
4.0%
Other values (29)1764
36.0%

_embedded.show.name
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct69
Distinct (%)69.7%
Missing0
Missing (%)0.0%
Memory size920.0 B
33 Ребёнка
12 
Obsolete
 
6
Countdown to I Do
 
4
Exit Nordpolen
 
3
New Face
 
2
Other values (64)
72 

Length

Max length36
Median length26
Mean length14.73737374
Min length5

Characters and Unicode

Total characters1459
Distinct characters93
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique56 ?
Unique (%)56.6%

Sample

1st rowSim for You
2nd rowКотики
3rd rowLAB с Антоном Беляевым
4th rowCore Sense
5th rowWu Shen Zhu Zai

Common Values

ValueCountFrequency (%)
33 Ребёнка12
 
12.1%
Obsolete6
 
6.1%
Countdown to I Do4
 
4.0%
Exit Nordpolen3
 
3.0%
New Face2
 
2.0%
To Love2
 
2.0%
Cheyenne et Lola2
 
2.0%
Something Just Like This2
 
2.0%
The Holiday Movies That Made Us2
 
2.0%
Please Wait, Brother2
 
2.0%
Other values (59)62
62.6%

Length

2022-09-05T21:35:45.703449image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
3312
 
4.6%
ребёнка12
 
4.6%
obsolete6
 
2.3%
to6
 
2.3%
i5
 
1.9%
the5
 
1.9%
a4
 
1.5%
countdown4
 
1.5%
do4
 
1.5%
of4
 
1.5%
Other values (159)197
76.1%

Most occurring characters

ValueCountFrequency (%)
160
 
11.0%
e127
 
8.7%
o92
 
6.3%
a82
 
5.6%
t72
 
4.9%
n63
 
4.3%
i62
 
4.2%
s58
 
4.0%
r47
 
3.2%
l47
 
3.2%
Other values (83)649
44.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1029
70.5%
Uppercase Letter231
 
15.8%
Space Separator160
 
11.0%
Decimal Number26
 
1.8%
Other Punctuation12
 
0.8%
Dash Punctuation1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e127
 
12.3%
o92
 
8.9%
a82
 
8.0%
t72
 
7.0%
n63
 
6.1%
i62
 
6.0%
s58
 
5.6%
r47
 
4.6%
l47
 
4.6%
h35
 
3.4%
Other values (42)344
33.4%
Uppercase Letter
ValueCountFrequency (%)
T24
 
10.4%
S15
 
6.5%
L14
 
6.1%
M13
 
5.6%
Р13
 
5.6%
A13
 
5.6%
C12
 
5.2%
N11
 
4.8%
F11
 
4.8%
D11
 
4.8%
Other values (21)94
40.7%
Other Punctuation
ValueCountFrequency (%)
.5
41.7%
,3
25.0%
'2
 
16.7%
:1
 
8.3%
&1
 
8.3%
Decimal Number
ValueCountFrequency (%)
324
92.3%
11
 
3.8%
01
 
3.8%
Space Separator
ValueCountFrequency (%)
160
100.0%
Dash Punctuation
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1112
76.2%
Common199
 
13.6%
Cyrillic148
 
10.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e127
 
11.4%
o92
 
8.3%
a82
 
7.4%
t72
 
6.5%
n63
 
5.7%
i62
 
5.6%
s58
 
5.2%
r47
 
4.2%
l47
 
4.2%
h35
 
3.1%
Other values (43)427
38.4%
Cyrillic
ValueCountFrequency (%)
е19
12.8%
н15
10.1%
к13
 
8.8%
Р13
 
8.8%
а13
 
8.8%
б12
 
8.1%
ё12
 
8.1%
о7
 
4.7%
в5
 
3.4%
т5
 
3.4%
Other values (20)34
23.0%
Common
ValueCountFrequency (%)
160
80.4%
324
 
12.1%
.5
 
2.5%
,3
 
1.5%
'2
 
1.0%
11
 
0.5%
01
 
0.5%
1
 
0.5%
:1
 
0.5%
&1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII1304
89.4%
Cyrillic148
 
10.1%
None6
 
0.4%
Punctuation1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
160
 
12.3%
e127
 
9.7%
o92
 
7.1%
a82
 
6.3%
t72
 
5.5%
n63
 
4.8%
i62
 
4.8%
s58
 
4.4%
r47
 
3.6%
l47
 
3.6%
Other values (48)494
37.9%
Cyrillic
ValueCountFrequency (%)
е19
12.8%
н15
10.1%
к13
 
8.8%
Р13
 
8.8%
а13
 
8.8%
б12
 
8.1%
ё12
 
8.1%
о7
 
4.7%
в5
 
3.4%
т5
 
3.4%
Other values (20)34
23.0%
None
ValueCountFrequency (%)
ø3
50.0%
ş1
 
16.7%
ı1
 
16.7%
á1
 
16.7%
Punctuation
ValueCountFrequency (%)
1
100.0%

_embedded.show.type
Categorical

HIGH CORRELATION

Distinct8
Distinct (%)8.1%
Missing0
Missing (%)0.0%
Memory size920.0 B
Scripted
49 
Documentary
12 
Animation
12 
Reality
Talk Show
Other values (3)
10 

Length

Max length11
Median length9
Mean length8.262626263
Min length4

Characters and Unicode

Total characters818
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowReality
2nd rowScripted
3rd rowDocumentary
4th rowAnimation
5th rowAnimation

Common Values

ValueCountFrequency (%)
Scripted49
49.5%
Documentary12
 
12.1%
Animation12
 
12.1%
Reality9
 
9.1%
Talk Show7
 
7.1%
Variety4
 
4.0%
Sports4
 
4.0%
News2
 
2.0%

Length

2022-09-05T21:35:45.802247image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:35:45.896158image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
scripted49
46.2%
documentary12
 
11.3%
animation12
 
11.3%
reality9
 
8.5%
talk7
 
6.6%
show7
 
6.6%
variety4
 
3.8%
sports4
 
3.8%
news2
 
1.9%

Most occurring characters

ValueCountFrequency (%)
t90
11.0%
i86
10.5%
e76
 
9.3%
r69
 
8.4%
c61
 
7.5%
S60
 
7.3%
p53
 
6.5%
d49
 
6.0%
a44
 
5.4%
n36
 
4.4%
Other values (16)194
23.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter705
86.2%
Uppercase Letter106
 
13.0%
Space Separator7
 
0.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t90
12.8%
i86
12.2%
e76
10.8%
r69
9.8%
c61
8.7%
p53
7.5%
d49
7.0%
a44
6.2%
n36
 
5.1%
o35
 
5.0%
Other values (8)106
15.0%
Uppercase Letter
ValueCountFrequency (%)
S60
56.6%
D12
 
11.3%
A12
 
11.3%
R9
 
8.5%
T7
 
6.6%
V4
 
3.8%
N2
 
1.9%
Space Separator
ValueCountFrequency (%)
7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin811
99.1%
Common7
 
0.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
t90
11.1%
i86
10.6%
e76
9.4%
r69
 
8.5%
c61
 
7.5%
S60
 
7.4%
p53
 
6.5%
d49
 
6.0%
a44
 
5.4%
n36
 
4.4%
Other values (15)187
23.1%
Common
ValueCountFrequency (%)
7
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII818
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t90
11.0%
i86
10.5%
e76
 
9.3%
r69
 
8.4%
c61
 
7.5%
S60
 
7.3%
p53
 
6.5%
d49
 
6.0%
a44
 
5.4%
n36
 
4.4%
Other values (16)194
23.7%

_embedded.show.language
Categorical

HIGH CORRELATION

Distinct14
Distinct (%)14.1%
Missing0
Missing (%)0.0%
Memory size920.0 B
English
28 
Russian
21 
Chinese
20 
Japanese
Norwegian
Other values (9)
15 

Length

Max length9
Median length7
Mean length7.121212121
Min length5

Characters and Unicode

Total characters705
Distinct characters30
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)4.0%

Sample

1st rowKorean
2nd rowRussian
3rd rowRussian
4th rowChinese
5th rowChinese

Common Values

ValueCountFrequency (%)
English28
28.3%
Russian21
21.2%
Chinese20
20.2%
Japanese9
 
9.1%
Norwegian6
 
6.1%
Arabic3
 
3.0%
Korean2
 
2.0%
Turkish2
 
2.0%
Spanish2
 
2.0%
French2
 
2.0%
Other values (4)4
 
4.0%

Length

2022-09-05T21:35:45.987207image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
english28
28.3%
russian21
21.2%
chinese20
20.2%
japanese9
 
9.1%
norwegian6
 
6.1%
arabic3
 
3.0%
korean2
 
2.0%
turkish2
 
2.0%
spanish2
 
2.0%
french2
 
2.0%
Other values (4)4
 
4.0%

Most occurring characters

ValueCountFrequency (%)
s105
14.9%
n91
12.9%
i84
11.9%
e70
9.9%
h56
7.9%
a55
7.8%
g36
 
5.1%
l29
 
4.1%
E28
 
4.0%
u24
 
3.4%
Other values (20)127
18.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter606
86.0%
Uppercase Letter99
 
14.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s105
17.3%
n91
15.0%
i84
13.9%
e70
11.6%
h56
9.2%
a55
9.1%
g36
 
5.9%
l29
 
4.8%
u24
 
4.0%
r16
 
2.6%
Other values (8)40
 
6.6%
Uppercase Letter
ValueCountFrequency (%)
E28
28.3%
R21
21.2%
C20
20.2%
J9
 
9.1%
N6
 
6.1%
A3
 
3.0%
T3
 
3.0%
S3
 
3.0%
K2
 
2.0%
F2
 
2.0%
Other values (2)2
 
2.0%

Most occurring scripts

ValueCountFrequency (%)
Latin705
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
s105
14.9%
n91
12.9%
i84
11.9%
e70
9.9%
h56
7.9%
a55
7.8%
g36
 
5.1%
l29
 
4.1%
E28
 
4.0%
u24
 
3.4%
Other values (20)127
18.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII705
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s105
14.9%
n91
12.9%
i84
11.9%
e70
9.9%
h56
7.9%
a55
7.8%
g36
 
5.1%
l29
 
4.1%
E28
 
4.0%
u24
 
3.4%
Other values (20)127
18.0%

_embedded.show.genres
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size920.0 B

_embedded.show.status
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size920.0 B
Ended
46 
Running
38 
To Be Determined
15 

Length

Max length16
Median length7
Mean length7.434343434
Min length5

Characters and Unicode

Total characters736
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowRunning
2nd rowEnded
3rd rowTo Be Determined
4th rowRunning
5th rowRunning

Common Values

ValueCountFrequency (%)
Ended46
46.5%
Running38
38.4%
To Be Determined15
 
15.2%

Length

2022-09-05T21:35:46.075949image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:35:46.155925image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
ended46
35.7%
running38
29.5%
to15
 
11.6%
be15
 
11.6%
determined15
 
11.6%

Most occurring characters

ValueCountFrequency (%)
n175
23.8%
d107
14.5%
e106
14.4%
i53
 
7.2%
E46
 
6.2%
R38
 
5.2%
u38
 
5.2%
g38
 
5.2%
30
 
4.1%
T15
 
2.0%
Other values (6)90
12.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter577
78.4%
Uppercase Letter129
 
17.5%
Space Separator30
 
4.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n175
30.3%
d107
18.5%
e106
18.4%
i53
 
9.2%
u38
 
6.6%
g38
 
6.6%
o15
 
2.6%
t15
 
2.6%
r15
 
2.6%
m15
 
2.6%
Uppercase Letter
ValueCountFrequency (%)
E46
35.7%
R38
29.5%
T15
 
11.6%
B15
 
11.6%
D15
 
11.6%
Space Separator
ValueCountFrequency (%)
30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin706
95.9%
Common30
 
4.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
n175
24.8%
d107
15.2%
e106
15.0%
i53
 
7.5%
E46
 
6.5%
R38
 
5.4%
u38
 
5.4%
g38
 
5.4%
T15
 
2.1%
o15
 
2.1%
Other values (5)75
10.6%
Common
ValueCountFrequency (%)
30
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII736
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n175
23.8%
d107
14.5%
e106
14.4%
i53
 
7.2%
E46
 
6.2%
R38
 
5.2%
u38
 
5.2%
g38
 
5.2%
30
 
4.1%
T15
 
2.0%
Other values (6)90
12.2%

_embedded.show.runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct24
Distinct (%)34.3%
Missing29
Missing (%)29.3%
Infinite0
Infinite (%)0.0%
Mean34.22857143
Minimum5
Maximum120
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size920.0 B
2022-09-05T21:35:46.226770image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile8.9
Q117
median30
Q345
95-th percentile60
Maximum120
Range115
Interquartile range (IQR)28

Descriptive statistics

Standard deviation22.22557049
Coefficient of variation (CV)0.6493280192
Kurtosis4.99135192
Mean34.22857143
Median Absolute Deviation (MAD)15
Skewness1.755590847
Sum2396
Variance493.9759834
MonotonicityNot monotonic
2022-09-05T21:35:46.323883image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
4515
15.2%
406
 
6.1%
136
 
6.1%
235
 
5.1%
254
 
4.0%
304
 
4.0%
153
 
3.0%
603
 
3.0%
503
 
3.0%
272
 
2.0%
Other values (14)19
19.2%
(Missing)29
29.3%
ValueCountFrequency (%)
52
 
2.0%
61
 
1.0%
81
 
1.0%
101
 
1.0%
122
 
2.0%
136
6.1%
141
 
1.0%
153
3.0%
161
 
1.0%
202
 
2.0%
ValueCountFrequency (%)
1202
 
2.0%
901
 
1.0%
603
 
3.0%
571
 
1.0%
503
 
3.0%
4515
15.2%
406
 
6.1%
372
 
2.0%
304
 
4.0%
272
 
2.0%

_embedded.show.averageRuntime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct34
Distinct (%)35.4%
Missing3
Missing (%)3.0%
Infinite0
Infinite (%)0.0%
Mean31.02083333
Minimum5
Maximum120
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size920.0 B
2022-09-05T21:35:46.412455image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile8.75
Q113
median25
Q345
95-th percentile66.75
Maximum120
Range115
Interquartile range (IQR)32

Descriptive statistics

Standard deviation22.61391242
Coefficient of variation (CV)0.7289911325
Kurtosis4.137491594
Mean31.02083333
Median Absolute Deviation (MAD)12
Skewness1.753261488
Sum2978
Variance511.3890351
MonotonicityNot monotonic
2022-09-05T21:35:46.515119image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
1319
19.2%
4516
16.2%
256
 
6.1%
234
 
4.0%
144
 
4.0%
503
 
3.0%
603
 
3.0%
263
 
3.0%
363
 
3.0%
123
 
3.0%
Other values (24)32
32.3%
(Missing)3
 
3.0%
ValueCountFrequency (%)
52
 
2.0%
62
 
2.0%
81
 
1.0%
91
 
1.0%
101
 
1.0%
111
 
1.0%
123
 
3.0%
1319
19.2%
144
 
4.0%
151
 
1.0%
ValueCountFrequency (%)
1202
 
2.0%
902
 
2.0%
871
 
1.0%
603
 
3.0%
591
 
1.0%
503
 
3.0%
471
 
1.0%
4516
16.2%
421
 
1.0%
401
 
1.0%

_embedded.show.premiered
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct51
Distinct (%)51.5%
Missing0
Missing (%)0.0%
Memory size920.0 B
2020-12-01
24 
2020-11-24
2019-12-03
2020-11-23
 
5
2020-10-20
 
5
Other values (46)
53 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters990
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)40.4%

Sample

1st row2019-03-25
2nd row2020-11-30
3rd row2019-12-17
4th row2020-10-13
5th row2020-03-08

Common Values

ValueCountFrequency (%)
2020-12-0124
24.2%
2020-11-246
 
6.1%
2019-12-036
 
6.1%
2020-11-235
 
5.1%
2020-10-205
 
5.1%
2020-11-173
 
3.0%
2020-11-192
 
2.0%
2020-10-132
 
2.0%
2020-11-302
 
2.0%
2020-11-032
 
2.0%
Other values (41)42
42.4%

Length

2022-09-05T21:35:46.599100image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-0124
24.2%
2019-12-036
 
6.1%
2020-11-246
 
6.1%
2020-11-235
 
5.1%
2020-10-205
 
5.1%
2020-11-173
 
3.0%
2020-11-302
 
2.0%
2020-11-082
 
2.0%
2020-11-032
 
2.0%
2020-10-132
 
2.0%
Other values (41)42
42.4%

Most occurring characters

ValueCountFrequency (%)
0256
25.9%
2231
23.3%
-198
20.0%
1186
18.8%
331
 
3.1%
929
 
2.9%
819
 
1.9%
414
 
1.4%
712
 
1.2%
510
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number792
80.0%
Dash Punctuation198
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0256
32.3%
2231
29.2%
1186
23.5%
331
 
3.9%
929
 
3.7%
819
 
2.4%
414
 
1.8%
712
 
1.5%
510
 
1.3%
64
 
0.5%
Dash Punctuation
ValueCountFrequency (%)
-198
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common990
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0256
25.9%
2231
23.3%
-198
20.0%
1186
18.8%
331
 
3.1%
929
 
2.9%
819
 
1.9%
414
 
1.4%
712
 
1.2%
510
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII990
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0256
25.9%
2231
23.3%
-198
20.0%
1186
18.8%
331
 
3.1%
929
 
2.9%
819
 
1.9%
414
 
1.4%
712
 
1.2%
510
 
1.0%

_embedded.show.ended
Categorical

HIGH CORRELATION
MISSING

Distinct18
Distinct (%)39.1%
Missing53
Missing (%)53.5%
Memory size920.0 B
2020-12-01
18 
2020-12-22
2020-12-03
2020-12-23
2020-12-16
Other values (13)
17 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters460
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)19.6%

Sample

1st row2020-12-11
2nd row2020-12-22
3rd row2020-12-08
4th row2020-12-08
5th row2020-12-01

Common Values

ValueCountFrequency (%)
2020-12-0118
 
18.2%
2020-12-225
 
5.1%
2020-12-032
 
2.0%
2020-12-232
 
2.0%
2020-12-162
 
2.0%
2020-12-022
 
2.0%
2020-12-302
 
2.0%
2020-12-152
 
2.0%
2020-12-082
 
2.0%
2020-12-111
 
1.0%
Other values (8)8
 
8.1%
(Missing)53
53.5%

Length

2022-09-05T21:35:46.673646image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-0118
39.1%
2020-12-225
 
10.9%
2020-12-032
 
4.3%
2020-12-232
 
4.3%
2020-12-162
 
4.3%
2020-12-022
 
4.3%
2020-12-302
 
4.3%
2020-12-152
 
4.3%
2020-12-082
 
4.3%
2020-12-051
 
2.2%
Other values (8)8
17.4%

Most occurring characters

ValueCountFrequency (%)
2153
33.3%
0119
25.9%
-92
20.0%
178
17.0%
36
 
1.3%
53
 
0.7%
83
 
0.7%
43
 
0.7%
62
 
0.4%
91
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number368
80.0%
Dash Punctuation92
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2153
41.6%
0119
32.3%
178
21.2%
36
 
1.6%
53
 
0.8%
83
 
0.8%
43
 
0.8%
62
 
0.5%
91
 
0.3%
Dash Punctuation
ValueCountFrequency (%)
-92
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common460
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2153
33.3%
0119
25.9%
-92
20.0%
178
17.0%
36
 
1.3%
53
 
0.7%
83
 
0.7%
43
 
0.7%
62
 
0.4%
91
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII460
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2153
33.3%
0119
25.9%
-92
20.0%
178
17.0%
36
 
1.3%
53
 
0.7%
83
 
0.7%
43
 
0.7%
62
 
0.4%
91
 
0.2%

_embedded.show.officialSite
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING

Distinct63
Distinct (%)69.2%
Missing8
Missing (%)8.1%
Memory size920.0 B
https://www.youtube.com/channel/UCVONgoOMPz54teymV2Jqwnw/videos
12 
https://project-obsolete.com/en/
 
6
https://www.discoveryplus.co.uk/show/countdown-to-i-do
 
4
https://tv.nrk.no/serie/exit-nordpolen
 
3
https://v.qq.com/detail/m/mzc00200tu76tos.html
 
2
Other values (58)
64 

Length

Max length97
Median length72
Mean length51.7032967
Min length18

Characters and Unicode

Total characters4705
Distinct characters74
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique52 ?
Unique (%)57.1%

Sample

1st rowhttps://www.vlive.tv/video/121637
2nd rowhttp://epic-media.ru/project/kotiki
3rd rowhttps://premier.one/show/lab-laboratoriya-muzyki-antona-belyaeva
4th rowhttps://www.bilibili.com/bangumi/media/md28223064
5th rowhttps://v.qq.com/detail/m/7q544xyrava3vxf.html

Common Values

ValueCountFrequency (%)
https://www.youtube.com/channel/UCVONgoOMPz54teymV2Jqwnw/videos12
 
12.1%
https://project-obsolete.com/en/6
 
6.1%
https://www.discoveryplus.co.uk/show/countdown-to-i-do4
 
4.0%
https://tv.nrk.no/serie/exit-nordpolen3
 
3.0%
https://v.qq.com/detail/m/mzc00200tu76tos.html2
 
2.0%
https://go.ocs.fr/details/serie/PSCHEYENNEEW01682592
 
2.0%
https://www.netflix.com/title/813372352
 
2.0%
https://v.qq.com/x/search/?q=+%E4%BB%8A%E5%A4%95%E4%BD%95%E5%A4%95&stag=0&smartbox_ab=2
 
2.0%
https://v.youku.com/v_show/id_XNDg2OTQ0ODAwOA==.html?s=dfbc7998206c499cac282
 
2.0%
https://www.iqiyi.com/a_19rrhskr95.html2
 
2.0%
Other values (53)54
54.5%
(Missing)8
 
8.1%

Length

2022-09-05T21:35:46.782369image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.youtube.com/channel/ucvongoompz54teymv2jqwnw/videos12
 
13.2%
https://project-obsolete.com/en6
 
6.6%
https://www.discoveryplus.co.uk/show/countdown-to-i-do4
 
4.4%
https://tv.nrk.no/serie/exit-nordpolen3
 
3.3%
https://v.qq.com/detail/m/mzc00200tu76tos.html2
 
2.2%
https://go.ocs.fr/details/serie/pscheyenneew01682592
 
2.2%
https://www.netflix.com/title/813372352
 
2.2%
https://v.qq.com/x/search/?q=+%e4%bb%8a%e5%a4%95%e4%bd%95%e5%a4%95&stag=0&smartbox_ab2
 
2.2%
https://v.youku.com/v_show/id_xndg2otq0odawoa==.html?s=dfbc7998206c499cac282
 
2.2%
https://www.iqiyi.com/a_19rrhskr95.html2
 
2.2%
Other values (53)54
59.3%

Most occurring characters

ValueCountFrequency (%)
/385
 
8.2%
t370
 
7.9%
o264
 
5.6%
e235
 
5.0%
s230
 
4.9%
w219
 
4.7%
.180
 
3.8%
h154
 
3.3%
c150
 
3.2%
i146
 
3.1%
Other values (64)2372
50.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3115
66.2%
Other Punctuation736
 
15.6%
Uppercase Letter396
 
8.4%
Decimal Number342
 
7.3%
Dash Punctuation69
 
1.5%
Math Symbol27
 
0.6%
Connector Punctuation20
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t370
 
11.9%
o264
 
8.5%
e235
 
7.5%
s230
 
7.4%
w219
 
7.0%
h154
 
4.9%
c150
 
4.8%
i146
 
4.7%
p142
 
4.6%
m123
 
3.9%
Other values (16)1082
34.7%
Uppercase Letter
ValueCountFrequency (%)
O38
 
9.6%
E32
 
8.1%
V29
 
7.3%
N28
 
7.1%
P27
 
6.8%
C26
 
6.6%
A22
 
5.6%
J20
 
5.1%
U20
 
5.1%
M15
 
3.8%
Other values (16)139
35.1%
Decimal Number
ValueCountFrequency (%)
248
14.0%
440
11.7%
939
11.4%
538
11.1%
036
10.5%
833
9.6%
129
8.5%
729
8.5%
626
7.6%
324
7.0%
Other Punctuation
ValueCountFrequency (%)
/385
52.3%
.180
24.5%
:91
 
12.4%
%57
 
7.7%
?16
 
2.2%
&5
 
0.7%
#1
 
0.1%
!1
 
0.1%
Math Symbol
ValueCountFrequency (%)
=25
92.6%
+2
 
7.4%
Dash Punctuation
ValueCountFrequency (%)
-69
100.0%
Connector Punctuation
ValueCountFrequency (%)
_20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3511
74.6%
Common1194
 
25.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
t370
 
10.5%
o264
 
7.5%
e235
 
6.7%
s230
 
6.6%
w219
 
6.2%
h154
 
4.4%
c150
 
4.3%
i146
 
4.2%
p142
 
4.0%
m123
 
3.5%
Other values (42)1478
42.1%
Common
ValueCountFrequency (%)
/385
32.2%
.180
15.1%
:91
 
7.6%
-69
 
5.8%
%57
 
4.8%
248
 
4.0%
440
 
3.4%
939
 
3.3%
538
 
3.2%
036
 
3.0%
Other values (12)211
17.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII4705
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/385
 
8.2%
t370
 
7.9%
o264
 
5.6%
e235
 
5.0%
s230
 
4.9%
w219
 
4.7%
.180
 
3.8%
h154
 
3.3%
c150
 
3.2%
i146
 
3.1%
Other values (64)2372
50.4%

_embedded.show.schedule.time
Categorical

HIGH CORRELATION

Distinct17
Distinct (%)17.2%
Missing0
Missing (%)0.0%
Memory size920.0 B
66 
20:00
06:00
 
5
10:00
 
3
20:40
 
2
Other values (12)
14 

Length

Max length5
Median length0
Mean length1.666666667
Min length0

Characters and Unicode

Total characters165
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)10.1%

Sample

1st row
2nd row10:00
3rd row23:45
4th row10:00
5th row10:00

Common Values

ValueCountFrequency (%)
66
66.7%
20:009
 
9.1%
06:005
 
5.1%
10:003
 
3.0%
20:402
 
2.0%
22:002
 
2.0%
12:002
 
2.0%
00:251
 
1.0%
08:301
 
1.0%
07:001
 
1.0%
Other values (7)7
 
7.1%

Length

2022-09-05T21:35:46.877276image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
20:009
27.3%
06:005
15.2%
10:003
 
9.1%
20:402
 
6.1%
22:002
 
6.1%
12:002
 
6.1%
00:251
 
3.0%
08:301
 
3.0%
07:001
 
3.0%
17:351
 
3.0%
Other values (6)6
18.2%

Most occurring characters

ValueCountFrequency (%)
083
50.3%
:33
 
20.0%
219
 
11.5%
19
 
5.5%
65
 
3.0%
54
 
2.4%
43
 
1.8%
33
 
1.8%
73
 
1.8%
82
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number132
80.0%
Other Punctuation33
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
083
62.9%
219
 
14.4%
19
 
6.8%
65
 
3.8%
54
 
3.0%
43
 
2.3%
33
 
2.3%
73
 
2.3%
82
 
1.5%
91
 
0.8%
Other Punctuation
ValueCountFrequency (%)
:33
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common165
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
083
50.3%
:33
 
20.0%
219
 
11.5%
19
 
5.5%
65
 
3.0%
54
 
2.4%
43
 
1.8%
33
 
1.8%
73
 
1.8%
82
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII165
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
083
50.3%
:33
 
20.0%
219
 
11.5%
19
 
5.5%
65
 
3.0%
54
 
2.4%
43
 
1.8%
33
 
1.8%
73
 
1.8%
82
 
1.2%

_embedded.show.schedule.days
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size920.0 B

_embedded.show.rating.average
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct3
Distinct (%)75.0%
Missing95
Missing (%)96.0%
Memory size920.0 B
6.8
5.8
5.6

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters12
Distinct characters4
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)50.0%

Sample

1st row6.8
2nd row6.8
3rd row5.8
4th row5.6

Common Values

ValueCountFrequency (%)
6.82
 
2.0%
5.81
 
1.0%
5.61
 
1.0%
(Missing)95
96.0%

Length

2022-09-05T21:35:46.957313image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:35:47.042557image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
6.82
50.0%
5.81
25.0%
5.61
25.0%

Most occurring characters

ValueCountFrequency (%)
.4
33.3%
63
25.0%
83
25.0%
52
16.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number8
66.7%
Other Punctuation4
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
63
37.5%
83
37.5%
52
25.0%
Other Punctuation
ValueCountFrequency (%)
.4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common12
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
.4
33.3%
63
25.0%
83
25.0%
52
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII12
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
.4
33.3%
63
25.0%
83
25.0%
52
16.7%

_embedded.show.weight
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct41
Distinct (%)41.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31.04040404
Minimum1
Maximum94
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size920.0 B
2022-09-05T21:35:47.127156image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.7
Q115
median31
Q334
95-th percentile80
Maximum94
Range93
Interquartile range (IQR)19

Descriptive statistics

Standard deviation20.05498523
Coefficient of variation (CV)0.6460929182
Kurtosis1.408633856
Mean31.04040404
Median Absolute Deviation (MAD)10
Skewness1.146364733
Sum3073
Variance402.2024325
MonotonicityNot monotonic
2022-09-05T21:35:47.228368image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
3420
20.2%
157
 
7.1%
75
 
5.1%
215
 
5.1%
303
 
3.0%
273
 
3.0%
313
 
3.0%
333
 
3.0%
323
 
3.0%
143
 
3.0%
Other values (31)44
44.4%
ValueCountFrequency (%)
12
 
2.0%
31
 
1.0%
42
 
2.0%
75
5.1%
82
 
2.0%
91
 
1.0%
101
 
1.0%
112
 
2.0%
131
 
1.0%
143
3.0%
ValueCountFrequency (%)
941
1.0%
871
1.0%
831
1.0%
821
1.0%
802
2.0%
741
1.0%
691
1.0%
631
1.0%
601
1.0%
591
1.0%

_embedded.show.network
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing99
Missing (%)100.0%
Memory size920.0 B

_embedded.show.webChannel.id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct34
Distinct (%)36.6%
Missing6
Missing (%)6.1%
Infinite0
Infinite (%)0.0%
Mean124.4731183
Minimum1
Maximum510
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size920.0 B
2022-09-05T21:35:47.320789image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile21
Q121
median67
Q3173
95-th percentile427.6
Maximum510
Range509
Interquartile range (IQR)152

Descriptive statistics

Standard deviation133.8062024
Coefficient of variation (CV)1.074980721
Kurtosis0.9123021568
Mean124.4731183
Median Absolute Deviation (MAD)46
Skewness1.365877153
Sum11576
Variance17904.09981
MonotonicityNot monotonic
2022-09-05T21:35:47.420976image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
2131
31.3%
1048
 
8.1%
436
 
6.1%
675
 
5.1%
2384
 
4.0%
1184
 
4.0%
1734
 
4.0%
3792
 
2.0%
12
 
2.0%
3272
 
2.0%
Other values (24)25
25.3%
(Missing)6
 
6.1%
ValueCountFrequency (%)
12
 
2.0%
21
 
1.0%
2131
31.3%
301
 
1.0%
436
 
6.1%
511
 
1.0%
541
 
1.0%
675
 
5.1%
991
 
1.0%
1021
 
1.0%
ValueCountFrequency (%)
5101
1.0%
5071
1.0%
4581
1.0%
4521
1.0%
4391
1.0%
4201
1.0%
3811
1.0%
3792
2.0%
3421
1.0%
3272
2.0%

_embedded.show.webChannel.name
Categorical

HIGH CORRELATION
MISSING

Distinct34
Distinct (%)36.6%
Missing6
Missing (%)6.1%
Memory size920.0 B
YouTube
31 
Tencent QQ
YouTube Premium
iQIYI
NRK TV
Other values (29)
39 

Length

Max length15
Median length14
Mean length7.752688172
Min length3

Characters and Unicode

Total characters721
Distinct characters56
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)24.7%

Sample

1st rowV LIVE
2nd rowEpic Media
3rd rowКиноПоиск HD
4th rowBilibili
5th rowTencent QQ

Common Values

ValueCountFrequency (%)
YouTube31
31.3%
Tencent QQ8
 
8.1%
YouTube Premium6
 
6.1%
iQIYI5
 
5.1%
NRK TV4
 
4.0%
Youku4
 
4.0%
discovery+4
 
4.0%
Shahid2
 
2.0%
Netflix2
 
2.0%
TV 2 Play2
 
2.0%
Other values (24)25
25.3%
(Missing)6
 
6.1%

Length

2022-09-05T21:35:47.514474image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
youtube37
30.1%
tencent8
 
6.5%
qq8
 
6.5%
premium6
 
4.9%
tv6
 
4.9%
iqiyi5
 
4.1%
nrk4
 
3.3%
youku4
 
3.3%
discovery4
 
3.3%
watch3
 
2.4%
Other values (33)38
30.9%

Most occurring characters

ValueCountFrequency (%)
u96
 
13.3%
e73
 
10.1%
T57
 
7.9%
o52
 
7.2%
Y46
 
6.4%
b43
 
6.0%
i33
 
4.6%
30
 
4.2%
t22
 
3.1%
Q21
 
2.9%
Other values (46)248
34.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter473
65.6%
Uppercase Letter208
28.8%
Space Separator30
 
4.2%
Math Symbol5
 
0.7%
Other Punctuation3
 
0.4%
Decimal Number2
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
u96
20.3%
e73
15.4%
o52
11.0%
b43
9.1%
i33
 
7.0%
t22
 
4.7%
a20
 
4.2%
c19
 
4.0%
n18
 
3.8%
m15
 
3.2%
Other values (18)82
17.3%
Uppercase Letter
ValueCountFrequency (%)
T57
27.4%
Y46
22.1%
Q21
 
10.1%
V14
 
6.7%
I12
 
5.8%
P11
 
5.3%
N7
 
3.4%
K5
 
2.4%
R5
 
2.4%
B4
 
1.9%
Other values (13)26
12.5%
Other Punctuation
ValueCountFrequency (%)
.2
66.7%
!1
33.3%
Space Separator
ValueCountFrequency (%)
30
100.0%
Math Symbol
ValueCountFrequency (%)
+5
100.0%
Decimal Number
ValueCountFrequency (%)
22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin672
93.2%
Common40
 
5.5%
Cyrillic9
 
1.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
u96
14.3%
e73
 
10.9%
T57
 
8.5%
o52
 
7.7%
Y46
 
6.8%
b43
 
6.4%
i33
 
4.9%
t22
 
3.3%
Q21
 
3.1%
a20
 
3.0%
Other values (34)209
31.1%
Cyrillic
ValueCountFrequency (%)
о2
22.2%
и2
22.2%
К1
11.1%
н1
11.1%
П1
11.1%
с1
11.1%
к1
11.1%
Common
ValueCountFrequency (%)
30
75.0%
+5
 
12.5%
.2
 
5.0%
22
 
5.0%
!1
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII712
98.8%
Cyrillic9
 
1.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
u96
13.5%
e73
 
10.3%
T57
 
8.0%
o52
 
7.3%
Y46
 
6.5%
b43
 
6.0%
i33
 
4.6%
30
 
4.2%
t22
 
3.1%
Q21
 
2.9%
Other values (39)239
33.6%
Cyrillic
ValueCountFrequency (%)
о2
22.2%
и2
22.2%
К1
11.1%
н1
11.1%
П1
11.1%
с1
11.1%
к1
11.1%

_embedded.show.webChannel.country.name
Categorical

HIGH CORRELATION
MISSING

Distinct11
Distinct (%)28.9%
Missing61
Missing (%)61.6%
Memory size920.0 B
China
13 
Norway
Russian Federation
United States
Korea, Republic of
Other values (6)

Length

Max length25
Median length18
Mean length9.342105263
Min length5

Characters and Unicode

Total characters355
Distinct characters35
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)10.5%

Sample

1st rowKorea, Republic of
2nd rowRussian Federation
3rd rowRussian Federation
4th rowChina
5th rowChina

Common Values

ValueCountFrequency (%)
China13
 
13.1%
Norway6
 
6.1%
Russian Federation5
 
5.1%
United States4
 
4.0%
Korea, Republic of2
 
2.0%
Japan2
 
2.0%
Turkey2
 
2.0%
Iran, Islamic Republic of1
 
1.0%
United Kingdom1
 
1.0%
Kazakhstan1
 
1.0%
(Missing)61
61.6%

Length

2022-09-05T21:35:47.606238image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
china13
23.6%
norway6
10.9%
russian5
 
9.1%
federation5
 
9.1%
united5
 
9.1%
states4
 
7.3%
republic3
 
5.5%
of3
 
5.5%
korea2
 
3.6%
japan2
 
3.6%
Other values (6)7
12.7%

Most occurring characters

ValueCountFrequency (%)
a44
 
12.4%
i33
 
9.3%
n33
 
9.3%
e26
 
7.3%
t20
 
5.6%
o17
 
4.8%
17
 
4.8%
s16
 
4.5%
r16
 
4.5%
h14
 
3.9%
Other values (25)119
33.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter283
79.7%
Uppercase Letter52
 
14.6%
Space Separator17
 
4.8%
Other Punctuation3
 
0.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a44
15.5%
i33
11.7%
n33
11.7%
e26
9.2%
t20
 
7.1%
o17
 
6.0%
s16
 
5.7%
r16
 
5.7%
h14
 
4.9%
d11
 
3.9%
Other values (12)53
18.7%
Uppercase Letter
ValueCountFrequency (%)
C13
25.0%
R8
15.4%
N6
11.5%
F5
 
9.6%
U5
 
9.6%
S4
 
7.7%
K4
 
7.7%
J2
 
3.8%
T2
 
3.8%
I2
 
3.8%
Space Separator
ValueCountFrequency (%)
17
100.0%
Other Punctuation
ValueCountFrequency (%)
,3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin335
94.4%
Common20
 
5.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
a44
13.1%
i33
 
9.9%
n33
 
9.9%
e26
 
7.8%
t20
 
6.0%
o17
 
5.1%
s16
 
4.8%
r16
 
4.8%
h14
 
4.2%
C13
 
3.9%
Other values (23)103
30.7%
Common
ValueCountFrequency (%)
17
85.0%
,3
 
15.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII355
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a44
 
12.4%
i33
 
9.3%
n33
 
9.3%
e26
 
7.3%
t20
 
5.6%
o17
 
4.8%
17
 
4.8%
s16
 
4.5%
r16
 
4.5%
h14
 
3.9%
Other values (25)119
33.5%

_embedded.show.webChannel.country.code
Categorical

HIGH CORRELATION
MISSING

Distinct11
Distinct (%)28.9%
Missing61
Missing (%)61.6%
Memory size920.0 B
CN
13 
NO
RU
US
KR
Other values (6)

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters76
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)10.5%

Sample

1st rowKR
2nd rowRU
3rd rowRU
4th rowCN
5th rowCN

Common Values

ValueCountFrequency (%)
CN13
 
13.1%
NO6
 
6.1%
RU5
 
5.1%
US4
 
4.0%
KR2
 
2.0%
JP2
 
2.0%
TR2
 
2.0%
IR1
 
1.0%
GB1
 
1.0%
KZ1
 
1.0%
(Missing)61
61.6%

Length

2022-09-05T21:35:47.691340image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
cn13
34.2%
no6
15.8%
ru5
 
13.2%
us4
 
10.5%
kr2
 
5.3%
jp2
 
5.3%
tr2
 
5.3%
ir1
 
2.6%
gb1
 
2.6%
kz1
 
2.6%

Most occurring characters

ValueCountFrequency (%)
N19
25.0%
C13
17.1%
R10
13.2%
U9
11.8%
O6
 
7.9%
S4
 
5.3%
K3
 
3.9%
J2
 
2.6%
P2
 
2.6%
T2
 
2.6%
Other values (5)6
 
7.9%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter76
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N19
25.0%
C13
17.1%
R10
13.2%
U9
11.8%
O6
 
7.9%
S4
 
5.3%
K3
 
3.9%
J2
 
2.6%
P2
 
2.6%
T2
 
2.6%
Other values (5)6
 
7.9%

Most occurring scripts

ValueCountFrequency (%)
Latin76
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N19
25.0%
C13
17.1%
R10
13.2%
U9
11.8%
O6
 
7.9%
S4
 
5.3%
K3
 
3.9%
J2
 
2.6%
P2
 
2.6%
T2
 
2.6%
Other values (5)6
 
7.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII76
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N19
25.0%
C13
17.1%
R10
13.2%
U9
11.8%
O6
 
7.9%
S4
 
5.3%
K3
 
3.9%
J2
 
2.6%
P2
 
2.6%
T2
 
2.6%
Other values (5)6
 
7.9%

_embedded.show.webChannel.country.timezone
Categorical

HIGH CORRELATION
MISSING

Distinct11
Distinct (%)28.9%
Missing61
Missing (%)61.6%
Memory size920.0 B
Asia/Shanghai
13 
Europe/Oslo
Asia/Kamchatka
America/New_York
Asia/Seoul
Other values (6)

Length

Max length16
Median length15
Mean length12.86842105
Min length10

Characters and Unicode

Total characters489
Distinct characters36
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)10.5%

Sample

1st rowAsia/Seoul
2nd rowAsia/Kamchatka
3rd rowAsia/Kamchatka
4th rowAsia/Shanghai
5th rowAsia/Shanghai

Common Values

ValueCountFrequency (%)
Asia/Shanghai13
 
13.1%
Europe/Oslo6
 
6.1%
Asia/Kamchatka5
 
5.1%
America/New_York4
 
4.0%
Asia/Seoul2
 
2.0%
Asia/Tokyo2
 
2.0%
Europe/Istanbul2
 
2.0%
Asia/Tehran1
 
1.0%
Europe/London1
 
1.0%
Asia/Qyzylorda1
 
1.0%
(Missing)61
61.6%

Length

2022-09-05T21:35:47.785572image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
asia/shanghai13
34.2%
europe/oslo6
15.8%
asia/kamchatka5
 
13.2%
america/new_york4
 
10.5%
asia/seoul2
 
5.3%
asia/tokyo2
 
5.3%
europe/istanbul2
 
5.3%
asia/tehran1
 
2.6%
europe/london1
 
2.6%
asia/qyzylorda1
 
2.6%

Most occurring characters

ValueCountFrequency (%)
a75
15.3%
i43
 
8.8%
/38
 
7.8%
h32
 
6.5%
s32
 
6.5%
A29
 
5.9%
o29
 
5.9%
r21
 
4.3%
e20
 
4.1%
n18
 
3.7%
Other values (26)152
31.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter367
75.1%
Uppercase Letter80
 
16.4%
Other Punctuation38
 
7.8%
Connector Punctuation4
 
0.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a75
20.4%
i43
11.7%
h32
8.7%
s32
8.7%
o29
 
7.9%
r21
 
5.7%
e20
 
5.4%
n18
 
4.9%
g13
 
3.5%
u13
 
3.5%
Other values (12)71
19.3%
Uppercase Letter
ValueCountFrequency (%)
A29
36.2%
S15
18.8%
E9
 
11.2%
O6
 
7.5%
K5
 
6.2%
N4
 
5.0%
Y4
 
5.0%
T3
 
3.8%
I2
 
2.5%
L1
 
1.2%
Other values (2)2
 
2.5%
Other Punctuation
ValueCountFrequency (%)
/38
100.0%
Connector Punctuation
ValueCountFrequency (%)
_4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin447
91.4%
Common42
 
8.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
a75
16.8%
i43
 
9.6%
h32
 
7.2%
s32
 
7.2%
A29
 
6.5%
o29
 
6.5%
r21
 
4.7%
e20
 
4.5%
n18
 
4.0%
S15
 
3.4%
Other values (24)133
29.8%
Common
ValueCountFrequency (%)
/38
90.5%
_4
 
9.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII489
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a75
15.3%
i43
 
8.8%
/38
 
7.8%
h32
 
6.5%
s32
 
6.5%
A29
 
5.9%
o29
 
5.9%
r21
 
4.3%
e20
 
4.1%
n18
 
3.7%
Other values (26)152
31.1%

_embedded.show.webChannel.officialSite
Categorical

HIGH CORRELATION
MISSING

Distinct11
Distinct (%)19.6%
Missing43
Missing (%)43.4%
Memory size920.0 B
https://www.youtube.com
31 
https://v.qq.com/
https://www.iq.com/
https://www.discoveryplus.com/
https://www.netflix.com/
 
2
Other values (6)

Length

Max length30
Median length23
Mean length22.35714286
Min length17

Characters and Unicode

Total characters1252
Distinct characters26
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)10.7%

Sample

1st rowhttps://www.vlive.tv/home
2nd rowhttps://hd.kinopoisk.ru/
3rd rowhttps://v.qq.com/
4th rowhttps://v.qq.com/
5th rowhttps://v.qq.com/

Common Values

ValueCountFrequency (%)
https://www.youtube.com31
31.3%
https://v.qq.com/8
 
8.1%
https://www.iq.com/5
 
5.1%
https://www.discoveryplus.com/4
 
4.0%
https://www.netflix.com/2
 
2.0%
https://www.vlive.tv/home1
 
1.0%
https://hd.kinopoisk.ru/1
 
1.0%
https://viaplay.com1
 
1.0%
https://tv.naver.com/1
 
1.0%
https://www.hulu.com/1
 
1.0%
(Missing)43
43.4%

Length

2022-09-05T21:35:47.879656image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.youtube.com31
55.4%
https://v.qq.com8
 
14.3%
https://www.iq.com5
 
8.9%
https://www.discoveryplus.com4
 
7.1%
https://www.netflix.com2
 
3.6%
https://www.vlive.tv/home1
 
1.8%
https://hd.kinopoisk.ru1
 
1.8%
https://viaplay.com1
 
1.8%
https://tv.naver.com1
 
1.8%
https://www.hulu.com1
 
1.8%

Most occurring characters

ValueCountFrequency (%)
t148
11.8%
/136
10.9%
w135
10.8%
.111
 
8.9%
o93
 
7.4%
u71
 
5.7%
s66
 
5.3%
p64
 
5.1%
h59
 
4.7%
c58
 
4.6%
Other values (16)311
24.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter949
75.8%
Other Punctuation303
 
24.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t148
15.6%
w135
14.2%
o93
9.8%
u71
7.5%
s66
7.0%
p64
6.7%
h59
 
6.2%
c58
 
6.1%
m56
 
5.9%
e40
 
4.2%
Other values (13)159
16.8%
Other Punctuation
ValueCountFrequency (%)
/136
44.9%
.111
36.6%
:56
18.5%

Most occurring scripts

ValueCountFrequency (%)
Latin949
75.8%
Common303
 
24.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
t148
15.6%
w135
14.2%
o93
9.8%
u71
7.5%
s66
7.0%
p64
6.7%
h59
 
6.2%
c58
 
6.1%
m56
 
5.9%
e40
 
4.2%
Other values (13)159
16.8%
Common
ValueCountFrequency (%)
/136
44.9%
.111
36.6%
:56
18.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII1252
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t148
11.8%
/136
10.9%
w135
10.8%
.111
 
8.9%
o93
 
7.4%
u71
 
5.7%
s66
 
5.3%
p64
 
5.1%
h59
 
4.7%
c58
 
4.6%
Other values (16)311
24.8%

_embedded.show.dvdCountry
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing99
Missing (%)100.0%
Memory size920.0 B

_embedded.show.externals.tvrage
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing98
Missing (%)99.0%
Memory size920.0 B
19056.0

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters7
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row19056.0

Common Values

ValueCountFrequency (%)
19056.01
 
1.0%
(Missing)98
99.0%

Length

2022-09-05T21:35:47.960672image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:35:48.032287image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
19056.01
100.0%

Most occurring characters

ValueCountFrequency (%)
02
28.6%
11
14.3%
91
14.3%
51
14.3%
61
14.3%
.1
14.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number6
85.7%
Other Punctuation1
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
02
33.3%
11
16.7%
91
16.7%
51
16.7%
61
16.7%
Other Punctuation
ValueCountFrequency (%)
.1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common7
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
02
28.6%
11
14.3%
91
14.3%
51
14.3%
61
14.3%
.1
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII7
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
02
28.6%
11
14.3%
91
14.3%
51
14.3%
61
14.3%
.1
14.3%

_embedded.show.externals.thetvdb
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct46
Distinct (%)79.3%
Missing41
Missing (%)41.4%
Infinite0
Infinite (%)0.0%
Mean356326.431
Minimum104271
Maximum419045
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size920.0 B
2022-09-05T21:35:48.113433image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum104271
5-th percentile272827.7
Q1341800.5
median372512.5
Q3392214
95-th percentile397742.3
Maximum419045
Range314774
Interquartile range (IQR)50413.5

Descriptive statistics

Standard deviation54599.16682
Coefficient of variation (CV)0.1532279451
Kurtosis6.74511956
Mean356326.431
Median Absolute Deviation (MAD)19896
Skewness-2.184607906
Sum20666933
Variance2981069018
MonotonicityNot monotonic
2022-09-05T21:35:48.221763image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
3703056
 
6.1%
3946183
 
3.0%
2813452
 
2.0%
3922142
 
2.0%
3914082
 
2.0%
3923622
 
2.0%
4087602
 
2.0%
3615411
 
1.0%
3501391
 
1.0%
3792721
 
1.0%
Other values (36)36
36.4%
(Missing)41
41.4%
ValueCountFrequency (%)
1042711
1.0%
2604361
1.0%
2651931
1.0%
2741751
1.0%
2743991
1.0%
2787931
1.0%
2813452
2.0%
2840461
1.0%
2879531
1.0%
2906861
1.0%
ValueCountFrequency (%)
4190451
 
1.0%
4087602
2.0%
3957981
 
1.0%
3946183
3.0%
3940451
 
1.0%
3926821
 
1.0%
3926491
 
1.0%
3924551
 
1.0%
3923622
2.0%
3922381
 
1.0%

_embedded.show.externals.imdb
Categorical

HIGH CORRELATION
MISSING

Distinct36
Distinct (%)72.0%
Missing49
Missing (%)49.5%
Memory size920.0 B
tt11398800
tt13939572
tt13570512
 
3
tt13439972
 
2
tt13539710
 
2
Other values (31)
33 

Length

Max length10
Median length10
Mean length9.78
Min length9

Characters and Unicode

Total characters489
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)58.0%

Sample

1st rowtt15127174
2nd rowtt11492320
3rd rowtt13570512
4th rowtt13570512
5th rowtt13570512

Common Values

ValueCountFrequency (%)
tt113988006
 
6.1%
tt139395724
 
4.0%
tt135705123
 
3.0%
tt134399722
 
2.0%
tt135397102
 
2.0%
tt113842182
 
2.0%
tt100944022
 
2.0%
tt17148101
 
1.0%
tt132548181
 
1.0%
tt00965971
 
1.0%
Other values (26)26
26.3%
(Missing)49
49.5%

Length

2022-09-05T21:35:48.319718image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
tt113988006
 
12.0%
tt139395724
 
8.0%
tt135705123
 
6.0%
tt134399722
 
4.0%
tt135397102
 
4.0%
tt113842182
 
4.0%
tt100944022
 
4.0%
tt112297481
 
2.0%
tt126609021
 
2.0%
tt136672301
 
2.0%
Other values (26)26
52.0%

Most occurring characters

ValueCountFrequency (%)
t100
20.4%
180
16.4%
052
10.6%
344
9.0%
244
9.0%
938
 
7.8%
834
 
7.0%
427
 
5.5%
525
 
5.1%
725
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number389
79.6%
Lowercase Letter100
 
20.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
180
20.6%
052
13.4%
344
11.3%
244
11.3%
938
9.8%
834
8.7%
427
 
6.9%
525
 
6.4%
725
 
6.4%
620
 
5.1%
Lowercase Letter
ValueCountFrequency (%)
t100
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common389
79.6%
Latin100
 
20.4%

Most frequent character per script

Common
ValueCountFrequency (%)
180
20.6%
052
13.4%
344
11.3%
244
11.3%
938
9.8%
834
8.7%
427
 
6.9%
525
 
6.4%
725
 
6.4%
620
 
5.1%
Latin
ValueCountFrequency (%)
t100
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII489
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t100
20.4%
180
16.4%
052
10.6%
344
9.0%
244
9.0%
938
 
7.8%
834
 
7.0%
427
 
5.5%
525
 
5.1%
725
 
5.1%

_embedded.show.image.medium
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING
UNIFORM

Distinct66
Distinct (%)77.6%
Missing14
Missing (%)14.1%
Memory size920.0 B
https://static.tvmaze.com/uploads/images/medium_portrait/230/576941.jpg
 
6
https://static.tvmaze.com/uploads/images/medium_portrait/317/794452.jpg
 
4
https://static.tvmaze.com/uploads/images/medium_portrait/287/717777.jpg
 
3
https://static.tvmaze.com/uploads/images/medium_portrait/285/713076.jpg
 
2
https://static.tvmaze.com/uploads/images/medium_portrait/285/714970.jpg
 
2
Other values (61)
68 

Length

Max length72
Median length71
Mean length71.01176471
Min length70

Characters and Unicode

Total characters6036
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique54 ?
Unique (%)63.5%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/medium_portrait/190/476668.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/medium_portrait/355/888089.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/medium_portrait/379/948045.jpg
4th rowhttps://static.tvmaze.com/uploads/images/medium_portrait/278/696645.jpg
5th rowhttps://static.tvmaze.com/uploads/images/medium_portrait/299/748854.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_portrait/230/576941.jpg6
 
6.1%
https://static.tvmaze.com/uploads/images/medium_portrait/317/794452.jpg4
 
4.0%
https://static.tvmaze.com/uploads/images/medium_portrait/287/717777.jpg3
 
3.0%
https://static.tvmaze.com/uploads/images/medium_portrait/285/713076.jpg2
 
2.0%
https://static.tvmaze.com/uploads/images/medium_portrait/285/714970.jpg2
 
2.0%
https://static.tvmaze.com/uploads/images/medium_portrait/285/714863.jpg2
 
2.0%
https://static.tvmaze.com/uploads/images/medium_portrait/285/713120.jpg2
 
2.0%
https://static.tvmaze.com/uploads/images/medium_portrait/285/713100.jpg2
 
2.0%
https://static.tvmaze.com/uploads/images/medium_portrait/285/713040.jpg2
 
2.0%
https://static.tvmaze.com/uploads/images/medium_portrait/284/711240.jpg2
 
2.0%
Other values (56)58
58.6%
(Missing)14
 
14.1%

Length

2022-09-05T21:35:48.409859image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_portrait/230/576941.jpg6
 
7.1%
https://static.tvmaze.com/uploads/images/medium_portrait/317/794452.jpg4
 
4.7%
https://static.tvmaze.com/uploads/images/medium_portrait/287/717777.jpg3
 
3.5%
https://static.tvmaze.com/uploads/images/medium_portrait/285/713100.jpg2
 
2.4%
https://static.tvmaze.com/uploads/images/medium_portrait/285/713798.jpg2
 
2.4%
https://static.tvmaze.com/uploads/images/medium_portrait/288/720951.jpg2
 
2.4%
https://static.tvmaze.com/uploads/images/medium_portrait/284/711240.jpg2
 
2.4%
https://static.tvmaze.com/uploads/images/medium_portrait/285/713040.jpg2
 
2.4%
https://static.tvmaze.com/uploads/images/medium_portrait/285/713120.jpg2
 
2.4%
https://static.tvmaze.com/uploads/images/medium_portrait/285/714863.jpg2
 
2.4%
Other values (56)58
68.2%

Most occurring characters

ValueCountFrequency (%)
t595
 
9.9%
/595
 
9.9%
m425
 
7.0%
a425
 
7.0%
p340
 
5.6%
s340
 
5.6%
i340
 
5.6%
o255
 
4.2%
.255
 
4.2%
e255
 
4.2%
Other values (22)2211
36.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4250
70.4%
Other Punctuation935
 
15.5%
Decimal Number766
 
12.7%
Connector Punctuation85
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t595
14.0%
m425
10.0%
a425
10.0%
p340
 
8.0%
s340
 
8.0%
i340
 
8.0%
o255
 
6.0%
e255
 
6.0%
u170
 
4.0%
c170
 
4.0%
Other values (8)935
22.0%
Decimal Number
ValueCountFrequency (%)
7103
13.4%
294
12.3%
191
11.9%
880
10.4%
574
9.7%
473
9.5%
370
9.1%
068
8.9%
961
8.0%
652
6.8%
Other Punctuation
ValueCountFrequency (%)
/595
63.6%
.255
27.3%
:85
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_85
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin4250
70.4%
Common1786
29.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
t595
14.0%
m425
10.0%
a425
10.0%
p340
 
8.0%
s340
 
8.0%
i340
 
8.0%
o255
 
6.0%
e255
 
6.0%
u170
 
4.0%
c170
 
4.0%
Other values (8)935
22.0%
Common
ValueCountFrequency (%)
/595
33.3%
.255
14.3%
7103
 
5.8%
294
 
5.3%
191
 
5.1%
_85
 
4.8%
:85
 
4.8%
880
 
4.5%
574
 
4.1%
473
 
4.1%
Other values (4)251
14.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII6036
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t595
 
9.9%
/595
 
9.9%
m425
 
7.0%
a425
 
7.0%
p340
 
5.6%
s340
 
5.6%
i340
 
5.6%
o255
 
4.2%
.255
 
4.2%
e255
 
4.2%
Other values (22)2211
36.6%

_embedded.show.image.original
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING
UNIFORM

Distinct66
Distinct (%)77.6%
Missing14
Missing (%)14.1%
Memory size920.0 B
https://static.tvmaze.com/uploads/images/original_untouched/230/576941.jpg
 
6
https://static.tvmaze.com/uploads/images/original_untouched/317/794452.jpg
 
4
https://static.tvmaze.com/uploads/images/original_untouched/287/717777.jpg
 
3
https://static.tvmaze.com/uploads/images/original_untouched/285/713076.jpg
 
2
https://static.tvmaze.com/uploads/images/original_untouched/285/714970.jpg
 
2
Other values (61)
68 

Length

Max length75
Median length74
Mean length74.01176471
Min length73

Characters and Unicode

Total characters6291
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique54 ?
Unique (%)63.5%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/original_untouched/190/476668.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/original_untouched/355/888089.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/original_untouched/379/948045.jpg
4th rowhttps://static.tvmaze.com/uploads/images/original_untouched/278/696645.jpg
5th rowhttps://static.tvmaze.com/uploads/images/original_untouched/299/748854.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/230/576941.jpg6
 
6.1%
https://static.tvmaze.com/uploads/images/original_untouched/317/794452.jpg4
 
4.0%
https://static.tvmaze.com/uploads/images/original_untouched/287/717777.jpg3
 
3.0%
https://static.tvmaze.com/uploads/images/original_untouched/285/713076.jpg2
 
2.0%
https://static.tvmaze.com/uploads/images/original_untouched/285/714970.jpg2
 
2.0%
https://static.tvmaze.com/uploads/images/original_untouched/285/714863.jpg2
 
2.0%
https://static.tvmaze.com/uploads/images/original_untouched/285/713120.jpg2
 
2.0%
https://static.tvmaze.com/uploads/images/original_untouched/285/713100.jpg2
 
2.0%
https://static.tvmaze.com/uploads/images/original_untouched/285/713040.jpg2
 
2.0%
https://static.tvmaze.com/uploads/images/original_untouched/284/711240.jpg2
 
2.0%
Other values (56)58
58.6%
(Missing)14
 
14.1%

Length

2022-09-05T21:35:48.505903image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/230/576941.jpg6
 
7.1%
https://static.tvmaze.com/uploads/images/original_untouched/317/794452.jpg4
 
4.7%
https://static.tvmaze.com/uploads/images/original_untouched/287/717777.jpg3
 
3.5%
https://static.tvmaze.com/uploads/images/original_untouched/285/713100.jpg2
 
2.4%
https://static.tvmaze.com/uploads/images/original_untouched/285/713798.jpg2
 
2.4%
https://static.tvmaze.com/uploads/images/original_untouched/288/720951.jpg2
 
2.4%
https://static.tvmaze.com/uploads/images/original_untouched/284/711240.jpg2
 
2.4%
https://static.tvmaze.com/uploads/images/original_untouched/285/713040.jpg2
 
2.4%
https://static.tvmaze.com/uploads/images/original_untouched/285/713120.jpg2
 
2.4%
https://static.tvmaze.com/uploads/images/original_untouched/285/714863.jpg2
 
2.4%
Other values (56)58
68.2%

Most occurring characters

ValueCountFrequency (%)
/595
 
9.5%
t510
 
8.1%
a425
 
6.8%
s340
 
5.4%
i340
 
5.4%
o340
 
5.4%
p255
 
4.1%
c255
 
4.1%
.255
 
4.1%
g255
 
4.1%
Other values (23)2721
43.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4505
71.6%
Other Punctuation935
 
14.9%
Decimal Number766
 
12.2%
Connector Punctuation85
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t510
 
11.3%
a425
 
9.4%
s340
 
7.5%
i340
 
7.5%
o340
 
7.5%
p255
 
5.7%
c255
 
5.7%
g255
 
5.7%
m255
 
5.7%
e255
 
5.7%
Other values (9)1275
28.3%
Decimal Number
ValueCountFrequency (%)
7103
13.4%
294
12.3%
191
11.9%
880
10.4%
574
9.7%
473
9.5%
370
9.1%
068
8.9%
961
8.0%
652
6.8%
Other Punctuation
ValueCountFrequency (%)
/595
63.6%
.255
27.3%
:85
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_85
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin4505
71.6%
Common1786
 
28.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
t510
 
11.3%
a425
 
9.4%
s340
 
7.5%
i340
 
7.5%
o340
 
7.5%
p255
 
5.7%
c255
 
5.7%
g255
 
5.7%
m255
 
5.7%
e255
 
5.7%
Other values (9)1275
28.3%
Common
ValueCountFrequency (%)
/595
33.3%
.255
14.3%
7103
 
5.8%
294
 
5.3%
191
 
5.1%
:85
 
4.8%
_85
 
4.8%
880
 
4.5%
574
 
4.1%
473
 
4.1%
Other values (4)251
14.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII6291
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/595
 
9.5%
t510
 
8.1%
a425
 
6.8%
s340
 
5.4%
i340
 
5.4%
o340
 
5.4%
p255
 
4.1%
c255
 
4.1%
.255
 
4.1%
g255
 
4.1%
Other values (23)2721
43.3%

_embedded.show.summary
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING

Distinct60
Distinct (%)68.2%
Missing11
Missing (%)11.1%
Memory size920.0 B
<p>A 12-episode online series about the funny and touching adventures of a student blogger who promotes the "child free" movement, but is forced to go to work as a volunteer nanny.</p>
12 
<p>In 2014, aliens revealed themselves to request trade with humanity. In exchange for limestone, they would provide a consciousness-controlled general-use robot known as an "EXOFRAME". Cheaper than an aircraft, tank, or firearm, and easy enough for anyone to operate, the "EXOFRAME" spreads change throughout the world in the blink of an eye...</p>
 
6
<p>Married couples think back to their dream weddings a year later and discuss all the choices they made. Revisiting the stress, cost and chaos, will these couples think it was all worth it for just one day?</p>
 
4
<p>When Børge Ousland goes on a trip, it's serious. Last autumn, he crossed the Arctic Ocean on skis. Everything did not go exactly according to plan. What happened along the way? <b>Exit Nordpolen</b> takes you on an insane expedition.</p>
 
3
<p>Unwrap the real stories behind these iconic Christmas blockbusters, thanks to insider interviews and behind-the-scenes peeks.</p>
 
2
Other values (55)
61 

Length

Max length1483
Median length419.5
Mean length310.625
Min length39

Characters and Unicode

Total characters27335
Distinct characters102
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49 ?
Unique (%)55.7%

Sample

1st row<p><b>Sim for You</b> is a reality series that chronicles each EXO member's life and reveal stories from their everyday life as a series.</p>
2nd row<p>Russian music artists reveal themselves from unexpected sides in the Anton Belyaev's show.</p>
3rd row<p>The power of beginnings, the energy of the core stone; one may find it good, one may find it evil. During a normal investigation, Yue Juntian finds himself drawn into the battle between the 'beginnings' of Yun City; Jiang Xin arrives in Yun City to stop Li Zunyuan's plan to take over. The two influence each other - one solves the mystery of their birth, the other redeems themselves. Together, they oppose Li Zunyuan.<br /> </p>
4th row<p>The protagonist Qin Chen, who was originally the top genius in the military domain, was conspired by the people to fall into the death canyon in the forbidden land of the mainland. Qin Chen, who was inevitably dead, unexpectedly triggered the power of the mysterious ancient sword.<br /><br />Three hundred years later, in a remote part of the Tianwu mainland, a boy of the same name accidentally inherited Qin Chen's will. As the beloved grandson of King Dingwu of the Daqi National Army, due to the birth father's birth, the mother and son were treated coldly in Dingwu's palace and lived together. In order to rewrite the myth of the strong man in hope of the sun, and to protect everything he loves, Qin Chen resolutely took up the responsibility of maintaining the five kingdoms of the world and set foot on the road of martial arts again.</p>
5th row<p>It's spin-off drama of <b>"Kono Koi Atatamemasu ka"</b></p>

Common Values

ValueCountFrequency (%)
<p>A 12-episode online series about the funny and touching adventures of a student blogger who promotes the "child free" movement, but is forced to go to work as a volunteer nanny.</p>12
 
12.1%
<p>In 2014, aliens revealed themselves to request trade with humanity. In exchange for limestone, they would provide a consciousness-controlled general-use robot known as an "EXOFRAME". Cheaper than an aircraft, tank, or firearm, and easy enough for anyone to operate, the "EXOFRAME" spreads change throughout the world in the blink of an eye...</p>6
 
6.1%
<p>Married couples think back to their dream weddings a year later and discuss all the choices they made. Revisiting the stress, cost and chaos, will these couples think it was all worth it for just one day?</p>4
 
4.0%
<p>When Børge Ousland goes on a trip, it's serious. Last autumn, he crossed the Arctic Ocean on skis. Everything did not go exactly according to plan. What happened along the way? <b>Exit Nordpolen</b> takes you on an insane expedition.</p>3
 
3.0%
<p>Unwrap the real stories behind these iconic Christmas blockbusters, thanks to insider interviews and behind-the-scenes peeks.</p>2
 
2.0%
<p>Cheyenne has been out of jail for six months now, working as a cleaner on the ferries whilst dreaming about traveling to the Amazon. Lola is a beautiful Parisian woman, selfish and ruthless, who has just arrived in the north of France to move in with her lover. But when Cheyenne witnesses Lola killing her lover's wife, she knows she's going to be accused of the crime because of her criminal past.</p>2
 
2.0%
<p>During the Yin Dynasty, Dong Yue, a brave general in the Dingyuan Rebellion, was sent back in time to stop a war that would claim the lives of countless innocents. She sets out to murder corrupted officer Lu Yuantong in an attempt to prevent war, and during her journey she met Feng Xi and Pang Yu. Pang Yu and Feng Xi were old friends who cared deeply for each other, but fell out and turn into enemies. While trying to reconcile the two brothers, Dong Yue also tries to stop Lu Yuantang's evil schemes which are poised to tear the nation apart with their help.</p>2
 
2.0%
<p>The police are investigating a case that involves a death directly caused by a rare bug known as the bullet ant. In order to clear his name, Tan Jingtian, an Insect toxicology graduate becomes involved in the bizzare investigation and collaborates with forensic doctor Jin Ling. As they dig deeper, they uncover the mystery behind his own identity.</p><p>Along with police captain Chen Han and the other detectives, they trace every clue as they solve one case at a time to uncover the murderer that has been in hiding for many years.</p>2
 
2.0%
<p>Pan, a desolate plastic surgeon, lived a repetitive and boring life every day until a conspiracy happened. He woke up in an abandoned factory, and found that someone had replaced his identity with a face exactly like him. His world has been completely overturned and left in a perilous situation. Can he overcome the difficulties and peel away the truth? How would he regain his identity?</p>2
 
2.0%
<p>Merchant Jiang Shuo and his odd specialist companion Qin Yi Heng purchase frequented houses to exchange them. In any case, alarming things start to occur and each spooky house is by all accounts part of a major riddle. Jiang Shuo, Yi Heng, and police officer Yuan Mu Qing attempt to understand the riddle.</p>2
 
2.0%
Other values (50)51
51.5%
(Missing)11
 
11.1%

Length

2022-09-05T21:35:48.629702image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the273
 
6.1%
and152
 
3.4%
to136
 
3.0%
a124
 
2.8%
of110
 
2.4%
in84
 
1.9%
is50
 
1.1%
with48
 
1.1%
as42
 
0.9%
an40
 
0.9%
Other values (1435)3443
76.5%

Most occurring characters

ValueCountFrequency (%)
4401
16.1%
e2685
 
9.8%
t1764
 
6.5%
o1615
 
5.9%
a1595
 
5.8%
n1591
 
5.8%
i1449
 
5.3%
s1354
 
5.0%
r1267
 
4.6%
h1025
 
3.7%
Other values (92)8589
31.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter20636
75.5%
Space Separator4414
 
16.1%
Uppercase Letter826
 
3.0%
Other Punctuation792
 
2.9%
Math Symbol510
 
1.9%
Decimal Number72
 
0.3%
Dash Punctuation63
 
0.2%
Other Letter13
 
< 0.1%
Open Punctuation4
 
< 0.1%
Close Punctuation4
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e2685
13.0%
t1764
 
8.5%
o1615
 
7.8%
a1595
 
7.7%
n1591
 
7.7%
i1449
 
7.0%
s1354
 
6.6%
r1267
 
6.1%
h1025
 
5.0%
l832
 
4.0%
Other values (23)5459
26.5%
Uppercase Letter
ValueCountFrequency (%)
A92
 
11.1%
T80
 
9.7%
I49
 
5.9%
E47
 
5.7%
M43
 
5.2%
C41
 
5.0%
H39
 
4.7%
Y39
 
4.7%
L35
 
4.2%
R34
 
4.1%
Other values (17)327
39.6%
Other Letter
ValueCountFrequency (%)
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
Other values (3)3
23.1%
Other Punctuation
ValueCountFrequency (%)
,269
34.0%
.235
29.7%
/132
16.7%
"61
 
7.7%
'55
 
6.9%
?15
 
1.9%
!11
 
1.4%
:6
 
0.8%
5
 
0.6%
;3
 
0.4%
Decimal Number
ValueCountFrequency (%)
124
33.3%
224
33.3%
013
18.1%
46
 
8.3%
71
 
1.4%
81
 
1.4%
51
 
1.4%
61
 
1.4%
31
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
-53
84.1%
9
 
14.3%
1
 
1.6%
Space Separator
ValueCountFrequency (%)
4401
99.7%
 13
 
0.3%
Math Symbol
ValueCountFrequency (%)
<255
50.0%
>255
50.0%
Open Punctuation
ValueCountFrequency (%)
(4
100.0%
Close Punctuation
ValueCountFrequency (%)
)4
100.0%
Initial Punctuation
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin21462
78.5%
Common5860
 
21.4%
Han13
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e2685
12.5%
t1764
 
8.2%
o1615
 
7.5%
a1595
 
7.4%
n1591
 
7.4%
i1449
 
6.8%
s1354
 
6.3%
r1267
 
5.9%
h1025
 
4.8%
l832
 
3.9%
Other values (50)6285
29.3%
Common
ValueCountFrequency (%)
4401
75.1%
,269
 
4.6%
<255
 
4.4%
>255
 
4.4%
.235
 
4.0%
/132
 
2.3%
"61
 
1.0%
'55
 
0.9%
-53
 
0.9%
124
 
0.4%
Other values (19)120
 
2.0%
Han
ValueCountFrequency (%)
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
Other values (3)3
23.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII27279
99.8%
None27
 
0.1%
Punctuation16
 
0.1%
CJK13
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4401
16.1%
e2685
 
9.8%
t1764
 
6.5%
o1615
 
5.9%
a1595
 
5.8%
n1591
 
5.8%
i1449
 
5.3%
s1354
 
5.0%
r1267
 
4.6%
h1025
 
3.8%
Other values (66)8533
31.3%
None
ValueCountFrequency (%)
 13
48.1%
ø5
 
18.5%
é2
 
7.4%
ü2
 
7.4%
ş1
 
3.7%
å1
 
3.7%
Ç1
 
3.7%
ö1
 
3.7%
á1
 
3.7%
Punctuation
ValueCountFrequency (%)
9
56.2%
5
31.2%
1
 
6.2%
1
 
6.2%
CJK
ValueCountFrequency (%)
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
Other values (3)3
23.1%

_embedded.show.updated
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct69
Distinct (%)69.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1640286587
Minimum1604587119
Maximum1662380496
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size920.0 B
2022-09-05T21:35:48.746027image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1604587119
5-th percentile1608351100
Q11630797304
median1646682390
Q31653642490
95-th percentile1661969503
Maximum1662380496
Range57793377
Interquartile range (IQR)22845186

Descriptive statistics

Standard deviation18220607.59
Coefficient of variation (CV)0.01110818544
Kurtosis-0.9101371023
Mean1640286587
Median Absolute Deviation (MAD)9337529
Skewness-0.6692458241
Sum1.623883722 × 1011
Variance3.319905408 × 1014
MonotonicityNot monotonic
2022-09-05T21:35:48.862696image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
165364249012
 
12.1%
16307973046
 
6.1%
16211903614
 
4.0%
16129761163
 
3.0%
16544453122
 
2.0%
16090607262
 
2.0%
16446505822
 
2.0%
16096068542
 
2.0%
16340498902
 
2.0%
16076979652
 
2.0%
Other values (59)62
62.6%
ValueCountFrequency (%)
16045871191
1.0%
16076979652
2.0%
16077170051
1.0%
16083343021
1.0%
16083529671
1.0%
16084062791
1.0%
16084990071
1.0%
16090607262
2.0%
16095351412
2.0%
16096068542
2.0%
ValueCountFrequency (%)
16623804961
1.0%
16623462771
1.0%
16622162831
1.0%
16621513691
1.0%
16619744211
1.0%
16619689571
1.0%
16618875351
1.0%
16618671131
1.0%
16617904371
1.0%
16614758321
1.0%

_embedded.show._links.self.href
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct69
Distinct (%)69.7%
Missing0
Missing (%)0.0%
Memory size920.0 B
https://api.tvmaze.com/shows/53282
12 
https://api.tvmaze.com/shows/45389
 
6
https://api.tvmaze.com/shows/55364
 
4
https://api.tvmaze.com/shows/51893
 
3
https://api.tvmaze.com/shows/52107
 
2
Other values (64)
72 

Length

Max length34
Median length34
Mean length33.97979798
Min length33

Characters and Unicode

Total characters3364
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique56 ?
Unique (%)56.6%

Sample

1st rowhttps://api.tvmaze.com/shows/41648
2nd rowhttps://api.tvmaze.com/shows/52198
3rd rowhttps://api.tvmaze.com/shows/52933
4th rowhttps://api.tvmaze.com/shows/51336
5th rowhttps://api.tvmaze.com/shows/54033

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/shows/5328212
 
12.1%
https://api.tvmaze.com/shows/453896
 
6.1%
https://api.tvmaze.com/shows/553644
 
4.0%
https://api.tvmaze.com/shows/518933
 
3.0%
https://api.tvmaze.com/shows/521072
 
2.0%
https://api.tvmaze.com/shows/521592
 
2.0%
https://api.tvmaze.com/shows/501062
 
2.0%
https://api.tvmaze.com/shows/518702
 
2.0%
https://api.tvmaze.com/shows/521642
 
2.0%
https://api.tvmaze.com/shows/520382
 
2.0%
Other values (59)62
62.6%

Length

2022-09-05T21:35:48.955585image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/shows/5328212
 
12.1%
https://api.tvmaze.com/shows/453896
 
6.1%
https://api.tvmaze.com/shows/553644
 
4.0%
https://api.tvmaze.com/shows/518933
 
3.0%
https://api.tvmaze.com/shows/521642
 
2.0%
https://api.tvmaze.com/shows/521062
 
2.0%
https://api.tvmaze.com/shows/521042
 
2.0%
https://api.tvmaze.com/shows/520382
 
2.0%
https://api.tvmaze.com/shows/521082
 
2.0%
https://api.tvmaze.com/shows/518702
 
2.0%
Other values (59)62
62.6%

Most occurring characters

ValueCountFrequency (%)
/396
 
11.8%
s297
 
8.8%
t297
 
8.8%
h198
 
5.9%
p198
 
5.9%
a198
 
5.9%
o198
 
5.9%
.198
 
5.9%
m198
 
5.9%
e99
 
2.9%
Other values (16)1087
32.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2178
64.7%
Other Punctuation693
 
20.6%
Decimal Number493
 
14.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s297
13.6%
t297
13.6%
h198
9.1%
p198
9.1%
a198
9.1%
o198
9.1%
m198
9.1%
e99
 
4.5%
w99
 
4.5%
c99
 
4.5%
Other values (3)297
13.6%
Decimal Number
ValueCountFrequency (%)
589
18.1%
267
13.6%
365
13.2%
162
12.6%
445
9.1%
844
8.9%
037
7.5%
636
7.3%
928
 
5.7%
720
 
4.1%
Other Punctuation
ValueCountFrequency (%)
/396
57.1%
.198
28.6%
:99
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin2178
64.7%
Common1186
35.3%

Most frequent character per script

Common
ValueCountFrequency (%)
/396
33.4%
.198
16.7%
:99
 
8.3%
589
 
7.5%
267
 
5.6%
365
 
5.5%
162
 
5.2%
445
 
3.8%
844
 
3.7%
037
 
3.1%
Other values (3)84
 
7.1%
Latin
ValueCountFrequency (%)
s297
13.6%
t297
13.6%
h198
9.1%
p198
9.1%
a198
9.1%
o198
9.1%
m198
9.1%
e99
 
4.5%
w99
 
4.5%
c99
 
4.5%
Other values (3)297
13.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII3364
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/396
 
11.8%
s297
 
8.8%
t297
 
8.8%
h198
 
5.9%
p198
 
5.9%
a198
 
5.9%
o198
 
5.9%
.198
 
5.9%
m198
 
5.9%
e99
 
2.9%
Other values (16)1087
32.3%

_embedded.show._links.previousepisode.href
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct69
Distinct (%)69.7%
Missing0
Missing (%)0.0%
Memory size920.0 B
https://api.tvmaze.com/episodes/2033295
12 
https://api.tvmaze.com/episodes/1978872
 
6
https://api.tvmaze.com/episodes/2093132
 
4
https://api.tvmaze.com/episodes/1969213
 
3
https://api.tvmaze.com/episodes/1976166
 
2
Other values (64)
72 

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters3861
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique56 ?
Unique (%)56.6%

Sample

1st rowhttps://api.tvmaze.com/episodes/1988862
2nd rowhttps://api.tvmaze.com/episodes/1986873
3rd rowhttps://api.tvmaze.com/episodes/2245512
4th rowhttps://api.tvmaze.com/episodes/1964569
5th rowhttps://api.tvmaze.com/episodes/2309442

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/203329512
 
12.1%
https://api.tvmaze.com/episodes/19788726
 
6.1%
https://api.tvmaze.com/episodes/20931324
 
4.0%
https://api.tvmaze.com/episodes/19692133
 
3.0%
https://api.tvmaze.com/episodes/19761662
 
2.0%
https://api.tvmaze.com/episodes/19776512
 
2.0%
https://api.tvmaze.com/episodes/19769342
 
2.0%
https://api.tvmaze.com/episodes/19685502
 
2.0%
https://api.tvmaze.com/episodes/19778102
 
2.0%
https://api.tvmaze.com/episodes/19735452
 
2.0%
Other values (59)62
62.6%

Length

2022-09-05T21:35:49.032761image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/203329512
 
12.1%
https://api.tvmaze.com/episodes/19788726
 
6.1%
https://api.tvmaze.com/episodes/20931324
 
4.0%
https://api.tvmaze.com/episodes/19692133
 
3.0%
https://api.tvmaze.com/episodes/19778102
 
2.0%
https://api.tvmaze.com/episodes/19761372
 
2.0%
https://api.tvmaze.com/episodes/19760542
 
2.0%
https://api.tvmaze.com/episodes/19735452
 
2.0%
https://api.tvmaze.com/episodes/19762022
 
2.0%
https://api.tvmaze.com/episodes/19685502
 
2.0%
Other values (59)62
62.6%

Most occurring characters

ValueCountFrequency (%)
/396
 
10.3%
t297
 
7.7%
p297
 
7.7%
s297
 
7.7%
e297
 
7.7%
a198
 
5.1%
i198
 
5.1%
.198
 
5.1%
m198
 
5.1%
o198
 
5.1%
Other values (16)1287
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2475
64.1%
Other Punctuation693
 
17.9%
Decimal Number693
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t297
12.0%
p297
12.0%
s297
12.0%
e297
12.0%
a198
8.0%
i198
8.0%
m198
8.0%
o198
8.0%
h99
 
4.0%
d99
 
4.0%
Other values (3)297
12.0%
Decimal Number
ValueCountFrequency (%)
2122
17.6%
390
13.0%
986
12.4%
186
12.4%
775
10.8%
053
7.6%
550
7.2%
850
7.2%
646
 
6.6%
435
 
5.1%
Other Punctuation
ValueCountFrequency (%)
/396
57.1%
.198
28.6%
:99
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin2475
64.1%
Common1386
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/396
28.6%
.198
14.3%
2122
 
8.8%
:99
 
7.1%
390
 
6.5%
986
 
6.2%
186
 
6.2%
775
 
5.4%
053
 
3.8%
550
 
3.6%
Other values (3)131
 
9.5%
Latin
ValueCountFrequency (%)
t297
12.0%
p297
12.0%
s297
12.0%
e297
12.0%
a198
8.0%
i198
8.0%
m198
8.0%
o198
8.0%
h99
 
4.0%
d99
 
4.0%
Other values (3)297
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII3861
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/396
 
10.3%
t297
 
7.7%
p297
 
7.7%
s297
 
7.7%
e297
 
7.7%
a198
 
5.1%
i198
 
5.1%
.198
 
5.1%
m198
 
5.1%
o198
 
5.1%
Other values (16)1287
33.3%

image.medium
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct26
Distinct (%)100.0%
Missing73
Missing (%)73.7%
Memory size920.0 B
https://static.tvmaze.com/uploads/images/medium_landscape/358/896916.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/289/724604.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/289/724603.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/285/712958.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/359/897951.jpg
 
1
Other values (21)
21 

Length

Max length73
Median length72
Mean length72.07692308
Min length72

Characters and Unicode

Total characters1874
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)100.0%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/medium_landscape/294/737206.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/medium_landscape/286/715105.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/medium_landscape/284/710997.jpg
4th rowhttps://static.tvmaze.com/uploads/images/medium_landscape/284/710998.jpg
5th rowhttps://static.tvmaze.com/uploads/images/medium_landscape/284/710999.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_landscape/358/896916.jpg1
 
1.0%
https://static.tvmaze.com/uploads/images/medium_landscape/289/724604.jpg1
 
1.0%
https://static.tvmaze.com/uploads/images/medium_landscape/289/724603.jpg1
 
1.0%
https://static.tvmaze.com/uploads/images/medium_landscape/285/712958.jpg1
 
1.0%
https://static.tvmaze.com/uploads/images/medium_landscape/359/897951.jpg1
 
1.0%
https://static.tvmaze.com/uploads/images/medium_landscape/284/710176.jpg1
 
1.0%
https://static.tvmaze.com/uploads/images/medium_landscape/403/1009865.jpg1
 
1.0%
https://static.tvmaze.com/uploads/images/medium_landscape/404/1012046.jpg1
 
1.0%
https://static.tvmaze.com/uploads/images/medium_landscape/317/794449.jpg1
 
1.0%
https://static.tvmaze.com/uploads/images/medium_landscape/317/794448.jpg1
 
1.0%
Other values (16)16
 
16.2%
(Missing)73
73.7%

Length

2022-09-05T21:35:49.110471image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_landscape/358/896916.jpg1
 
3.8%
https://static.tvmaze.com/uploads/images/medium_landscape/289/724604.jpg1
 
3.8%
https://static.tvmaze.com/uploads/images/medium_landscape/286/715105.jpg1
 
3.8%
https://static.tvmaze.com/uploads/images/medium_landscape/284/710997.jpg1
 
3.8%
https://static.tvmaze.com/uploads/images/medium_landscape/284/710998.jpg1
 
3.8%
https://static.tvmaze.com/uploads/images/medium_landscape/284/710999.jpg1
 
3.8%
https://static.tvmaze.com/uploads/images/medium_landscape/286/715032.jpg1
 
3.8%
https://static.tvmaze.com/uploads/images/medium_landscape/285/714313.jpg1
 
3.8%
https://static.tvmaze.com/uploads/images/medium_landscape/286/715068.jpg1
 
3.8%
https://static.tvmaze.com/uploads/images/medium_landscape/287/719812.jpg1
 
3.8%
Other values (16)16
61.5%

Most occurring characters

ValueCountFrequency (%)
/182
 
9.7%
a156
 
8.3%
s130
 
6.9%
m130
 
6.9%
t130
 
6.9%
p104
 
5.5%
e104
 
5.5%
i78
 
4.2%
c78
 
4.2%
.78
 
4.2%
Other values (22)704
37.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1326
70.8%
Other Punctuation286
 
15.3%
Decimal Number236
 
12.6%
Connector Punctuation26
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a156
11.8%
s130
9.8%
m130
9.8%
t130
9.8%
p104
 
7.8%
e104
 
7.8%
i78
 
5.9%
c78
 
5.9%
d78
 
5.9%
l52
 
3.9%
Other values (8)286
21.6%
Decimal Number
ValueCountFrequency (%)
735
14.8%
928
11.9%
127
11.4%
826
11.0%
426
11.0%
225
10.6%
020
8.5%
618
7.6%
517
7.2%
314
 
5.9%
Other Punctuation
ValueCountFrequency (%)
/182
63.6%
.78
27.3%
:26
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1326
70.8%
Common548
29.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
a156
11.8%
s130
9.8%
m130
9.8%
t130
9.8%
p104
 
7.8%
e104
 
7.8%
i78
 
5.9%
c78
 
5.9%
d78
 
5.9%
l52
 
3.9%
Other values (8)286
21.6%
Common
ValueCountFrequency (%)
/182
33.2%
.78
14.2%
735
 
6.4%
928
 
5.1%
127
 
4.9%
826
 
4.7%
426
 
4.7%
_26
 
4.7%
:26
 
4.7%
225
 
4.6%
Other values (4)69
 
12.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII1874
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/182
 
9.7%
a156
 
8.3%
s130
 
6.9%
m130
 
6.9%
t130
 
6.9%
p104
 
5.5%
e104
 
5.5%
i78
 
4.2%
c78
 
4.2%
.78
 
4.2%
Other values (22)704
37.6%

image.original
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct26
Distinct (%)100.0%
Missing73
Missing (%)73.7%
Memory size920.0 B
https://static.tvmaze.com/uploads/images/original_untouched/358/896916.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/289/724604.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/289/724603.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/285/712958.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/359/897951.jpg
 
1
Other values (21)
21 

Length

Max length75
Median length74
Mean length74.07692308
Min length74

Characters and Unicode

Total characters1926
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)100.0%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/original_untouched/294/737206.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/original_untouched/286/715105.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/original_untouched/284/710997.jpg
4th rowhttps://static.tvmaze.com/uploads/images/original_untouched/284/710998.jpg
5th rowhttps://static.tvmaze.com/uploads/images/original_untouched/284/710999.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/358/896916.jpg1
 
1.0%
https://static.tvmaze.com/uploads/images/original_untouched/289/724604.jpg1
 
1.0%
https://static.tvmaze.com/uploads/images/original_untouched/289/724603.jpg1
 
1.0%
https://static.tvmaze.com/uploads/images/original_untouched/285/712958.jpg1
 
1.0%
https://static.tvmaze.com/uploads/images/original_untouched/359/897951.jpg1
 
1.0%
https://static.tvmaze.com/uploads/images/original_untouched/284/710176.jpg1
 
1.0%
https://static.tvmaze.com/uploads/images/original_untouched/403/1009865.jpg1
 
1.0%
https://static.tvmaze.com/uploads/images/original_untouched/404/1012046.jpg1
 
1.0%
https://static.tvmaze.com/uploads/images/original_untouched/317/794449.jpg1
 
1.0%
https://static.tvmaze.com/uploads/images/original_untouched/317/794448.jpg1
 
1.0%
Other values (16)16
 
16.2%
(Missing)73
73.7%

Length

2022-09-05T21:35:49.190664image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/358/896916.jpg1
 
3.8%
https://static.tvmaze.com/uploads/images/original_untouched/289/724604.jpg1
 
3.8%
https://static.tvmaze.com/uploads/images/original_untouched/286/715105.jpg1
 
3.8%
https://static.tvmaze.com/uploads/images/original_untouched/284/710997.jpg1
 
3.8%
https://static.tvmaze.com/uploads/images/original_untouched/284/710998.jpg1
 
3.8%
https://static.tvmaze.com/uploads/images/original_untouched/284/710999.jpg1
 
3.8%
https://static.tvmaze.com/uploads/images/original_untouched/286/715032.jpg1
 
3.8%
https://static.tvmaze.com/uploads/images/original_untouched/285/714313.jpg1
 
3.8%
https://static.tvmaze.com/uploads/images/original_untouched/286/715068.jpg1
 
3.8%
https://static.tvmaze.com/uploads/images/original_untouched/287/719812.jpg1
 
3.8%
Other values (16)16
61.5%

Most occurring characters

ValueCountFrequency (%)
/182
 
9.4%
t156
 
8.1%
a130
 
6.7%
s104
 
5.4%
i104
 
5.4%
o104
 
5.4%
p78
 
4.0%
c78
 
4.0%
.78
 
4.0%
g78
 
4.0%
Other values (23)834
43.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1378
71.5%
Other Punctuation286
 
14.8%
Decimal Number236
 
12.3%
Connector Punctuation26
 
1.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t156
 
11.3%
a130
 
9.4%
s104
 
7.5%
i104
 
7.5%
o104
 
7.5%
p78
 
5.7%
c78
 
5.7%
g78
 
5.7%
m78
 
5.7%
e78
 
5.7%
Other values (9)390
28.3%
Decimal Number
ValueCountFrequency (%)
735
14.8%
928
11.9%
127
11.4%
826
11.0%
426
11.0%
225
10.6%
020
8.5%
618
7.6%
517
7.2%
314
 
5.9%
Other Punctuation
ValueCountFrequency (%)
/182
63.6%
.78
27.3%
:26
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1378
71.5%
Common548
 
28.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
t156
 
11.3%
a130
 
9.4%
s104
 
7.5%
i104
 
7.5%
o104
 
7.5%
p78
 
5.7%
c78
 
5.7%
g78
 
5.7%
m78
 
5.7%
e78
 
5.7%
Other values (9)390
28.3%
Common
ValueCountFrequency (%)
/182
33.2%
.78
14.2%
735
 
6.4%
928
 
5.1%
127
 
4.9%
:26
 
4.7%
_26
 
4.7%
826
 
4.7%
426
 
4.7%
225
 
4.6%
Other values (4)69
 
12.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII1926
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/182
 
9.4%
t156
 
8.1%
a130
 
6.7%
s104
 
5.4%
i104
 
5.4%
o104
 
5.4%
p78
 
4.0%
c78
 
4.0%
.78
 
4.0%
g78
 
4.0%
Other values (23)834
43.3%

_embedded.show.network.id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct12
Distinct (%)92.3%
Missing86
Missing (%)86.9%
Infinite0
Infinite (%)0.0%
Mean703.1538462
Minimum85
Maximum1683
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size920.0 B
2022-09-05T21:35:49.262675image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum85
5-th percentile101.2
Q1205
median432
Q31282
95-th percentile1614.6
Maximum1683
Range1598
Interquartile range (IQR)1077

Descriptive statistics

Standard deviation589.8431778
Coefficient of variation (CV)0.8388536605
Kurtosis-1.378247627
Mean703.1538462
Median Absolute Deviation (MAD)320
Skewness0.6005634438
Sum9141
Variance347914.9744
MonotonicityNot monotonic
2022-09-05T21:35:49.344268image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
4322
 
2.0%
3081
 
1.0%
12821
 
1.0%
5141
 
1.0%
15691
 
1.0%
16831
 
1.0%
851
 
1.0%
1591
 
1.0%
2051
 
1.0%
13541
 
1.0%
Other values (2)2
 
2.0%
(Missing)86
86.9%
ValueCountFrequency (%)
851
1.0%
1121
1.0%
1591
1.0%
2051
1.0%
3081
1.0%
4322
2.0%
5141
1.0%
10061
1.0%
12821
1.0%
13541
1.0%
ValueCountFrequency (%)
16831
1.0%
15691
1.0%
13541
1.0%
12821
1.0%
10061
1.0%
5141
1.0%
4322
2.0%
3081
1.0%
2051
1.0%
1591
1.0%

_embedded.show.network.name
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct12
Distinct (%)92.3%
Missing86
Missing (%)86.9%
Memory size920.0 B
OCS Max
ТНТ
CCTV-1
ТВ-3
Суббота
Other values (7)

Length

Max length11
Median length7
Mean length5.846153846
Min length3

Characters and Unicode

Total characters76
Distinct characters40
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)84.6%

Sample

1st rowТНТ
2nd rowCCTV-1
3rd rowТВ-3
4th rowСуббота
5th rowDMC

Common Values

ValueCountFrequency (%)
OCS Max2
 
2.0%
ТНТ1
 
1.0%
CCTV-11
 
1.0%
ТВ-31
 
1.0%
Суббота1
 
1.0%
DMC1
 
1.0%
PBS1
 
1.0%
TBS1
 
1.0%
NFL Network1
 
1.0%
Fuji TV TWO1
 
1.0%
Other values (2)2
 
2.0%
(Missing)86
86.9%

Length

2022-09-05T21:35:49.436119image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
ocs2
 
10.5%
max2
 
10.5%
tv2
 
10.5%
тнт1
 
5.3%
cctv-11
 
5.3%
тв-31
 
5.3%
суббота1
 
5.3%
dmc1
 
5.3%
pbs1
 
5.3%
tbs1
 
5.3%
Other values (6)6
31.6%

Most occurring characters

ValueCountFrequency (%)
6
 
7.9%
T6
 
7.9%
C5
 
6.6%
S4
 
5.3%
V4
 
5.3%
O3
 
3.9%
M3
 
3.9%
Т3
 
3.9%
б2
 
2.6%
L2
 
2.6%
Other values (30)38
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter43
56.6%
Lowercase Letter22
28.9%
Space Separator6
 
7.9%
Decimal Number3
 
3.9%
Dash Punctuation2
 
2.6%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
T6
14.0%
C5
11.6%
S4
9.3%
V4
9.3%
O3
 
7.0%
M3
 
7.0%
Т3
 
7.0%
L2
 
4.7%
F2
 
4.7%
N2
 
4.7%
Other values (8)9
20.9%
Lowercase Letter
ValueCountFrequency (%)
б2
 
9.1%
i2
 
9.1%
x2
 
9.1%
a2
 
9.1%
e2
 
9.1%
t1
 
4.5%
j1
 
4.5%
u1
 
4.5%
k1
 
4.5%
r1
 
4.5%
Other values (7)7
31.8%
Decimal Number
ValueCountFrequency (%)
31
33.3%
11
33.3%
41
33.3%
Space Separator
ValueCountFrequency (%)
6
100.0%
Dash Punctuation
ValueCountFrequency (%)
-2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin53
69.7%
Cyrillic12
 
15.8%
Common11
 
14.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
T6
 
11.3%
C5
 
9.4%
S4
 
7.5%
V4
 
7.5%
O3
 
5.7%
M3
 
5.7%
L2
 
3.8%
F2
 
3.8%
N2
 
3.8%
B2
 
3.8%
Other values (16)20
37.7%
Cyrillic
ValueCountFrequency (%)
Т3
25.0%
б2
16.7%
а1
 
8.3%
т1
 
8.3%
о1
 
8.3%
у1
 
8.3%
С1
 
8.3%
В1
 
8.3%
Н1
 
8.3%
Common
ValueCountFrequency (%)
6
54.5%
-2
 
18.2%
31
 
9.1%
11
 
9.1%
41
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII64
84.2%
Cyrillic12
 
15.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6
 
9.4%
T6
 
9.4%
C5
 
7.8%
S4
 
6.2%
V4
 
6.2%
O3
 
4.7%
M3
 
4.7%
L2
 
3.1%
F2
 
3.1%
N2
 
3.1%
Other values (21)27
42.2%
Cyrillic
ValueCountFrequency (%)
Т3
25.0%
б2
16.7%
а1
 
8.3%
т1
 
8.3%
о1
 
8.3%
у1
 
8.3%
С1
 
8.3%
В1
 
8.3%
Н1
 
8.3%

_embedded.show.network.country.name
Categorical

HIGH CORRELATION
MISSING

Distinct7
Distinct (%)53.8%
Missing86
Missing (%)86.9%
Memory size920.0 B
Russian Federation
United States
Japan
France
China
Other values (2)

Length

Max length18
Median length13
Mean length10.46153846
Min length5

Characters and Unicode

Total characters136
Distinct characters25
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)23.1%

Sample

1st rowRussian Federation
2nd rowChina
3rd rowRussian Federation
4th rowRussian Federation
5th rowEgypt

Common Values

ValueCountFrequency (%)
Russian Federation3
 
3.0%
United States3
 
3.0%
Japan2
 
2.0%
France2
 
2.0%
China1
 
1.0%
Egypt1
 
1.0%
Netherlands1
 
1.0%
(Missing)86
86.9%

Length

2022-09-05T21:35:49.525357image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:35:49.620012image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
russian3
15.8%
federation3
15.8%
united3
15.8%
states3
15.8%
japan2
10.5%
france2
10.5%
china1
 
5.3%
egypt1
 
5.3%
netherlands1
 
5.3%

Most occurring characters

ValueCountFrequency (%)
a17
12.5%
e16
11.8%
n15
11.0%
t14
10.3%
s10
 
7.4%
i10
 
7.4%
d7
 
5.1%
6
 
4.4%
r6
 
4.4%
F5
 
3.7%
Other values (15)30
22.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter111
81.6%
Uppercase Letter19
 
14.0%
Space Separator6
 
4.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a17
15.3%
e16
14.4%
n15
13.5%
t14
12.6%
s10
9.0%
i10
9.0%
d7
6.3%
r6
 
5.4%
p3
 
2.7%
o3
 
2.7%
Other values (6)10
9.0%
Uppercase Letter
ValueCountFrequency (%)
F5
26.3%
R3
15.8%
S3
15.8%
U3
15.8%
J2
 
10.5%
C1
 
5.3%
E1
 
5.3%
N1
 
5.3%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin130
95.6%
Common6
 
4.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
a17
13.1%
e16
12.3%
n15
11.5%
t14
10.8%
s10
 
7.7%
i10
 
7.7%
d7
 
5.4%
r6
 
4.6%
F5
 
3.8%
R3
 
2.3%
Other values (14)27
20.8%
Common
ValueCountFrequency (%)
6
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII136
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a17
12.5%
e16
11.8%
n15
11.0%
t14
10.3%
s10
 
7.4%
i10
 
7.4%
d7
 
5.1%
6
 
4.4%
r6
 
4.4%
F5
 
3.7%
Other values (15)30
22.1%

_embedded.show.network.country.code
Categorical

HIGH CORRELATION
MISSING

Distinct7
Distinct (%)53.8%
Missing86
Missing (%)86.9%
Memory size920.0 B
RU
US
JP
FR
CN
Other values (2)

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters26
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)23.1%

Sample

1st rowRU
2nd rowCN
3rd rowRU
4th rowRU
5th rowEG

Common Values

ValueCountFrequency (%)
RU3
 
3.0%
US3
 
3.0%
JP2
 
2.0%
FR2
 
2.0%
CN1
 
1.0%
EG1
 
1.0%
NL1
 
1.0%
(Missing)86
86.9%

Length

2022-09-05T21:35:49.700750image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:35:49.794540image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
ru3
23.1%
us3
23.1%
jp2
15.4%
fr2
15.4%
cn1
 
7.7%
eg1
 
7.7%
nl1
 
7.7%

Most occurring characters

ValueCountFrequency (%)
U6
23.1%
R5
19.2%
S3
11.5%
J2
 
7.7%
P2
 
7.7%
F2
 
7.7%
N2
 
7.7%
C1
 
3.8%
E1
 
3.8%
G1
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter26
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
U6
23.1%
R5
19.2%
S3
11.5%
J2
 
7.7%
P2
 
7.7%
F2
 
7.7%
N2
 
7.7%
C1
 
3.8%
E1
 
3.8%
G1
 
3.8%

Most occurring scripts

ValueCountFrequency (%)
Latin26
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
U6
23.1%
R5
19.2%
S3
11.5%
J2
 
7.7%
P2
 
7.7%
F2
 
7.7%
N2
 
7.7%
C1
 
3.8%
E1
 
3.8%
G1
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII26
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
U6
23.1%
R5
19.2%
S3
11.5%
J2
 
7.7%
P2
 
7.7%
F2
 
7.7%
N2
 
7.7%
C1
 
3.8%
E1
 
3.8%
G1
 
3.8%

_embedded.show.network.country.timezone
Categorical

HIGH CORRELATION
MISSING

Distinct7
Distinct (%)53.8%
Missing86
Missing (%)86.9%
Memory size920.0 B
Asia/Kamchatka
America/New_York
Asia/Tokyo
Europe/Paris
Asia/Shanghai
Other values (2)

Length

Max length16
Median length14
Mean length13.46153846
Min length10

Characters and Unicode

Total characters175
Distinct characters30
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)23.1%

Sample

1st rowAsia/Kamchatka
2nd rowAsia/Shanghai
3rd rowAsia/Kamchatka
4th rowAsia/Kamchatka
5th rowAfrica/Cairo

Common Values

ValueCountFrequency (%)
Asia/Kamchatka3
 
3.0%
America/New_York3
 
3.0%
Asia/Tokyo2
 
2.0%
Europe/Paris2
 
2.0%
Asia/Shanghai1
 
1.0%
Africa/Cairo1
 
1.0%
Europe/Amsterdam1
 
1.0%
(Missing)86
86.9%

Length

2022-09-05T21:35:49.881747image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:35:49.978069image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
asia/kamchatka3
23.1%
america/new_york3
23.1%
asia/tokyo2
15.4%
europe/paris2
15.4%
asia/shanghai1
 
7.7%
africa/cairo1
 
7.7%
europe/amsterdam1
 
7.7%

Most occurring characters

ValueCountFrequency (%)
a25
14.3%
i14
 
8.0%
r14
 
8.0%
/13
 
7.4%
A11
 
6.3%
o11
 
6.3%
e10
 
5.7%
s9
 
5.1%
m8
 
4.6%
k8
 
4.6%
Other values (20)52
29.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter130
74.3%
Uppercase Letter29
 
16.6%
Other Punctuation13
 
7.4%
Connector Punctuation3
 
1.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a25
19.2%
i14
10.8%
r14
10.8%
o11
8.5%
e10
 
7.7%
s9
 
6.9%
m8
 
6.2%
k8
 
6.2%
c7
 
5.4%
h5
 
3.8%
Other values (9)19
14.6%
Uppercase Letter
ValueCountFrequency (%)
A11
37.9%
E3
 
10.3%
Y3
 
10.3%
N3
 
10.3%
K3
 
10.3%
T2
 
6.9%
P2
 
6.9%
S1
 
3.4%
C1
 
3.4%
Other Punctuation
ValueCountFrequency (%)
/13
100.0%
Connector Punctuation
ValueCountFrequency (%)
_3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin159
90.9%
Common16
 
9.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a25
15.7%
i14
 
8.8%
r14
 
8.8%
A11
 
6.9%
o11
 
6.9%
e10
 
6.3%
s9
 
5.7%
m8
 
5.0%
k8
 
5.0%
c7
 
4.4%
Other values (18)42
26.4%
Common
ValueCountFrequency (%)
/13
81.2%
_3
 
18.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII175
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a25
14.3%
i14
 
8.0%
r14
 
8.0%
/13
 
7.4%
A11
 
6.3%
o11
 
6.3%
e10
 
5.7%
s9
 
5.1%
m8
 
4.6%
k8
 
4.6%
Other values (20)52
29.7%

_embedded.show.network.officialSite
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing99
Missing (%)100.0%
Memory size920.0 B

_embedded.show._links.nextepisode.href
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct6
Distinct (%)100.0%
Missing93
Missing (%)93.9%
Memory size920.0 B
https://api.tvmaze.com/episodes/2309443
https://api.tvmaze.com/episodes/2384253
https://api.tvmaze.com/episodes/2375640
https://api.tvmaze.com/episodes/2383184
https://api.tvmaze.com/episodes/2383145

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters234
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/2309443
2nd rowhttps://api.tvmaze.com/episodes/2384253
3rd rowhttps://api.tvmaze.com/episodes/2375640
4th rowhttps://api.tvmaze.com/episodes/2383184
5th rowhttps://api.tvmaze.com/episodes/2383145

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/23094431
 
1.0%
https://api.tvmaze.com/episodes/23842531
 
1.0%
https://api.tvmaze.com/episodes/23756401
 
1.0%
https://api.tvmaze.com/episodes/23831841
 
1.0%
https://api.tvmaze.com/episodes/23831451
 
1.0%
https://api.tvmaze.com/episodes/23797031
 
1.0%
(Missing)93
93.9%

Length

2022-09-05T21:35:50.059338image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:35:50.149568image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/23094431
16.7%
https://api.tvmaze.com/episodes/23842531
16.7%
https://api.tvmaze.com/episodes/23756401
16.7%
https://api.tvmaze.com/episodes/23831841
16.7%
https://api.tvmaze.com/episodes/23831451
16.7%
https://api.tvmaze.com/episodes/23797031
16.7%

Most occurring characters

ValueCountFrequency (%)
/24
 
10.3%
p18
 
7.7%
s18
 
7.7%
e18
 
7.7%
t18
 
7.7%
a12
 
5.1%
i12
 
5.1%
.12
 
5.1%
m12
 
5.1%
o12
 
5.1%
Other values (16)78
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter150
64.1%
Other Punctuation42
 
17.9%
Decimal Number42
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p18
12.0%
s18
12.0%
e18
12.0%
t18
12.0%
a12
8.0%
i12
8.0%
m12
8.0%
o12
8.0%
h6
 
4.0%
d6
 
4.0%
Other values (3)18
12.0%
Decimal Number
ValueCountFrequency (%)
311
26.2%
27
16.7%
46
14.3%
84
 
9.5%
03
 
7.1%
53
 
7.1%
73
 
7.1%
92
 
4.8%
12
 
4.8%
61
 
2.4%
Other Punctuation
ValueCountFrequency (%)
/24
57.1%
.12
28.6%
:6
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin150
64.1%
Common84
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/24
28.6%
.12
14.3%
311
13.1%
27
 
8.3%
46
 
7.1%
:6
 
7.1%
84
 
4.8%
03
 
3.6%
53
 
3.6%
73
 
3.6%
Other values (3)5
 
6.0%
Latin
ValueCountFrequency (%)
p18
12.0%
s18
12.0%
e18
12.0%
t18
12.0%
a12
8.0%
i12
8.0%
m12
8.0%
o12
8.0%
h6
 
4.0%
d6
 
4.0%
Other values (3)18
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII234
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/24
 
10.3%
p18
 
7.7%
s18
 
7.7%
e18
 
7.7%
t18
 
7.7%
a12
 
5.1%
i12
 
5.1%
.12
 
5.1%
m12
 
5.1%
o12
 
5.1%
Other values (16)78
33.3%

_embedded.show.webChannel
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing99
Missing (%)100.0%
Memory size920.0 B

_embedded.show.image
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing99
Missing (%)100.0%
Memory size920.0 B

_embedded.show.webChannel.country
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing99
Missing (%)100.0%
Memory size920.0 B

_embedded.show.dvdCountry.name
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing98
Missing (%)99.0%
Memory size920.0 B
Japan

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters5
Distinct characters4
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowJapan

Common Values

ValueCountFrequency (%)
Japan1
 
1.0%
(Missing)98
99.0%

Length

2022-09-05T21:35:50.232329image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:35:50.306574image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
japan1
100.0%

Most occurring characters

ValueCountFrequency (%)
a2
40.0%
J1
20.0%
p1
20.0%
n1
20.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4
80.0%
Uppercase Letter1
 
20.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a2
50.0%
p1
25.0%
n1
25.0%
Uppercase Letter
ValueCountFrequency (%)
J1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin5
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a2
40.0%
J1
20.0%
p1
20.0%
n1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII5
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a2
40.0%
J1
20.0%
p1
20.0%
n1
20.0%

_embedded.show.dvdCountry.code
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing98
Missing (%)99.0%
Memory size920.0 B
JP

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowJP

Common Values

ValueCountFrequency (%)
JP1
 
1.0%
(Missing)98
99.0%

Length

2022-09-05T21:35:50.371020image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:35:50.442739image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
jp1
100.0%

Most occurring characters

ValueCountFrequency (%)
J1
50.0%
P1
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter2
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
J1
50.0%
P1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
J1
50.0%
P1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
J1
50.0%
P1
50.0%

_embedded.show.dvdCountry.timezone
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing98
Missing (%)99.0%
Memory size920.0 B
Asia/Tokyo

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters10
Distinct characters9
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowAsia/Tokyo

Common Values

ValueCountFrequency (%)
Asia/Tokyo1
 
1.0%
(Missing)98
99.0%

Length

2022-09-05T21:35:50.871279image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:35:50.944358image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
asia/tokyo1
100.0%

Most occurring characters

ValueCountFrequency (%)
o2
20.0%
A1
10.0%
s1
10.0%
i1
10.0%
a1
10.0%
/1
10.0%
T1
10.0%
k1
10.0%
y1
10.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter7
70.0%
Uppercase Letter2
 
20.0%
Other Punctuation1
 
10.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o2
28.6%
s1
14.3%
i1
14.3%
a1
14.3%
k1
14.3%
y1
14.3%
Uppercase Letter
ValueCountFrequency (%)
A1
50.0%
T1
50.0%
Other Punctuation
ValueCountFrequency (%)
/1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin9
90.0%
Common1
 
10.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
o2
22.2%
A1
11.1%
s1
11.1%
i1
11.1%
a1
11.1%
T1
11.1%
k1
11.1%
y1
11.1%
Common
ValueCountFrequency (%)
/1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII10
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o2
20.0%
A1
10.0%
s1
10.0%
i1
10.0%
a1
10.0%
/1
10.0%
T1
10.0%
k1
10.0%
y1
10.0%

Interactions

2022-09-05T21:35:40.550452image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:31.378630image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:32.187788image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:33.124427image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:33.917866image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:34.708780image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:35.616553image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:36.418722image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:37.225658image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:38.165217image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:38.949731image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:39.752076image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:40.622482image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:31.452331image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:32.256547image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:33.189196image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:33.980474image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:34.777583image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:35.678242image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:36.481632image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:37.290963image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:38.226827image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:39.012042image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:39.819762image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:40.692701image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:31.528294image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:32.327540image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:33.261196image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:34.052353image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:34.847183image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:35.750214image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:36.556023image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:37.357686image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:38.301926image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:39.084870image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:39.889891image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:40.757858image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:31.594218image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:32.395746image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:33.325552image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:34.116185image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:35.013597image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:35.824420image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:36.623043image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:37.420854image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:38.365722image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:39.149971image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:39.954743image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:41.028485image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:31.659120image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:32.466116image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:33.389948image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:34.180393image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:35.084198image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:35.889268image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:36.688754image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:37.482540image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:38.429426image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:39.215287image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:40.019239image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:41.105412image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:31.737983image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:32.535393image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:33.459073image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:34.253641image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:35.150226image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:35.954044image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:36.757963image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:37.707778image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:38.494213image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:39.287617image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:40.089143image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:41.172492image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:31.800467image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:32.603278image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:33.525370image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:34.318372image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:35.215165image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:36.021804image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:36.826486image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:37.785513image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:38.559195image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:39.353306image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:40.155193image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:41.241913image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:31.863059image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:32.671569image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:33.590744image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:34.383845image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:35.289030image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:36.088389image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:36.895783image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:37.848744image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:38.625295image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:39.419389image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:40.221814image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:41.308688image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:31.924576image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:32.745410image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:33.652942image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:34.444606image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:35.351289image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:36.149016image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:36.957189image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:37.908612image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:38.685324image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:39.481006image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:40.285984image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:41.368809image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:31.988025image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:32.914328image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:33.720380image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:34.508543image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:35.413655image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:36.212086image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:37.024456image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:37.970636image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:38.750187image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:39.550583image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:40.353844image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:41.435785image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:32.050922image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:32.987270image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:33.788310image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:34.577089image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:35.479510image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:36.284796image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:37.091547image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:38.038182image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:38.824974image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:39.618347image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:40.420755image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:41.500040image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:32.115614image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:33.055645image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:33.853766image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:34.642423image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:35.548711image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:36.351660image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:37.157447image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:38.101399image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:38.888393image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:39.683541image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:35:40.485195image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Correlations

2022-09-05T21:35:51.031583image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-09-05T21:35:51.288518image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-09-05T21:35:51.512920image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-09-05T21:35:51.780451image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-09-05T21:35:41.852681image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2022-09-05T21:35:42.538065image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
2022-09-05T21:35:43.020161image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

idurlnameseasonnumbertypeairdateairtimeairstampruntimeimagesummaryrating.average_links.self.href_embedded.show.id_embedded.show.url_embedded.show.name_embedded.show.type_embedded.show.language_embedded.show.genres_embedded.show.status_embedded.show.runtime_embedded.show.averageRuntime_embedded.show.premiered_embedded.show.ended_embedded.show.officialSite_embedded.show.schedule.time_embedded.show.schedule.days_embedded.show.rating.average_embedded.show.weight_embedded.show.network_embedded.show.webChannel.id_embedded.show.webChannel.name_embedded.show.webChannel.country.name_embedded.show.webChannel.country.code_embedded.show.webChannel.country.timezone_embedded.show.webChannel.officialSite_embedded.show.dvdCountry_embedded.show.externals.tvrage_embedded.show.externals.thetvdb_embedded.show.externals.imdb_embedded.show.image.medium_embedded.show.image.original_embedded.show.summary_embedded.show.updated_embedded.show._links.self.href_embedded.show._links.previousepisode.hrefimage.mediumimage.original_embedded.show.network.id_embedded.show.network.name_embedded.show.network.country.name_embedded.show.network.country.code_embedded.show.network.country.timezone_embedded.show.network.officialSite_embedded.show._links.nextepisode.href_embedded.show.webChannel_embedded.show.image_embedded.show.webChannel.country_embedded.show.dvdCountry.name_embedded.show.dvdCountry.code_embedded.show.dvdCountry.timezone
01979824https://www.tvmaze.com/episodes/1979824/sim-for-you-4x16-chanyeols-episode-16Chanyeol's Episode 16416regular2020-12-0106:002020-11-30T21:00:00+00:0016.0NaN<p><b>#ObtainedAConversationalSkill #WeSetUpATent♥ #ManySmiles</b></p>NaNhttps://api.tvmaze.com/episodes/197982441648https://www.tvmaze.com/shows/41648/sim-for-youSim for YouRealityKorean[]Running16.016.02019-03-25Nonehttps://www.vlive.tv/video/121637[Monday, Wednesday, Friday]NaN29NaN122.0V LIVEKorea, Republic ofKRAsia/Seoulhttps://www.vlive.tv/homeNaNNaN361541.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/190/476668.jpghttps://static.tvmaze.com/uploads/images/original_untouched/190/476668.jpg<p><b>Sim for You</b> is a reality series that chronicles each EXO member's life and reveal stories from their everyday life as a series.</p>1608499007https://api.tvmaze.com/shows/41648https://api.tvmaze.com/episodes/1988862NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
11979222https://www.tvmaze.com/episodes/1979222/kotiki-1x02-seria-2Серия 212regular2020-12-012020-12-01T00:00:00+00:0012.0NaNNoneNaNhttps://api.tvmaze.com/episodes/197922252198https://www.tvmaze.com/shows/52198/kotikiКотикиScriptedRussian[Comedy]Ended12.012.02020-11-302020-12-11http://epic-media.ru/project/kotiki10:00[Monday, Tuesday, Wednesday, Thursday, Friday]NaN15NaN510.0Epic MediaRussian FederationRUAsia/KamchatkaNoneNaNNaN392682.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/355/888089.jpghttps://static.tvmaze.com/uploads/images/original_untouched/355/888089.jpgNone1637555191https://api.tvmaze.com/shows/52198https://api.tvmaze.com/episodes/1986873NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
22008027https://www.tvmaze.com/episodes/2008027/lab-s-antonom-belaevym-2x06-lolitaЛолита26regular2020-12-012020-12-01T00:00:00+00:0029.0NaNNoneNaNhttps://api.tvmaze.com/episodes/200802752933https://www.tvmaze.com/shows/52933/lab-s-antonom-belaevymLAB с Антоном БеляевымDocumentaryRussian[Music]To Be Determined26.025.02019-12-17Nonehttps://premier.one/show/lab-laboratoriya-muzyki-antona-belyaeva23:45[Saturday]NaN25NaN381.0КиноПоиск HDRussian FederationRUAsia/Kamchatkahttps://hd.kinopoisk.ru/NaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/379/948045.jpghttps://static.tvmaze.com/uploads/images/original_untouched/379/948045.jpg<p>Russian music artists reveal themselves from unexpected sides in the Anton Belyaev's show.</p>1654035738https://api.tvmaze.com/shows/52933https://api.tvmaze.com/episodes/2245512https://static.tvmaze.com/uploads/images/medium_landscape/294/737206.jpghttps://static.tvmaze.com/uploads/images/original_untouched/294/737206.jpg308.0ТНТRussian FederationRUAsia/KamchatkaNaNNaNNaNNaNNaNNaNNaNNaN
31964565https://www.tvmaze.com/episodes/1964565/core-sense-1x09-episode-9Episode 919regular2020-12-0110:002020-12-01T02:00:00+00:0024.0NaNNoneNaNhttps://api.tvmaze.com/episodes/196456551336https://www.tvmaze.com/shows/51336/core-senseCore SenseAnimationChinese[Action, Anime, Science-Fiction]Running24.024.02020-10-13Nonehttps://www.bilibili.com/bangumi/media/md2822306410:00[Tuesday]NaN29NaN51.0BilibiliChinaCNAsia/ShanghaiNoneNaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/278/696645.jpghttps://static.tvmaze.com/uploads/images/original_untouched/278/696645.jpg<p>The power of beginnings, the energy of the core stone; one may find it good, one may find it evil. During a normal investigation, Yue Juntian finds himself drawn into the battle between the 'beginnings' of Yun City; Jiang Xin arrives in Yun City to stop Li Zunyuan's plan to take over. The two influence each other - one solves the mystery of their birth, the other redeems themselves. Together, they oppose Li Zunyuan.<br /> </p>1604587119https://api.tvmaze.com/shows/51336https://api.tvmaze.com/episodes/1964569NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
42052503https://www.tvmaze.com/episodes/2052503/wu-shen-zhu-zai-1x80-episode-80Episode 80180regular2020-12-0110:002020-12-01T02:00:00+00:008.0NaNNoneNaNhttps://api.tvmaze.com/episodes/205250354033https://www.tvmaze.com/shows/54033/wu-shen-zhu-zaiWu Shen Zhu ZaiAnimationChinese[Action, Adventure, Anime, Fantasy]Running8.08.02020-03-08Nonehttps://v.qq.com/detail/m/7q544xyrava3vxf.html10:00[Tuesday, Sunday]NaN82NaN104.0Tencent QQChinaCNAsia/Shanghaihttps://v.qq.com/NaNNaN379070.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/299/748854.jpghttps://static.tvmaze.com/uploads/images/original_untouched/299/748854.jpg<p>The protagonist Qin Chen, who was originally the top genius in the military domain, was conspired by the people to fall into the death canyon in the forbidden land of the mainland. Qin Chen, who was inevitably dead, unexpectedly triggered the power of the mysterious ancient sword.<br /><br />Three hundred years later, in a remote part of the Tianwu mainland, a boy of the same name accidentally inherited Qin Chen's will. As the beloved grandson of King Dingwu of the Daqi National Army, due to the birth father's birth, the mother and son were treated coldly in Dingwu's palace and lived together. In order to rewrite the myth of the strong man in hope of the sun, and to protect everything he loves, Qin Chen resolutely took up the responsibility of maintaining the five kingdoms of the world and set foot on the road of martial arts again.</p>1649423444https://api.tvmaze.com/shows/54033https://api.tvmaze.com/episodes/2309442NaNNaNNaNNaNNaNNaNNaNNaNhttps://api.tvmaze.com/episodes/2309443NaNNaNNaNNaNNaNNaN
52315116https://www.tvmaze.com/episodes/2315116/sono-koi-mousukoshi-atatamemasuka-1x05-episode-5Episode 515regular2020-12-012020-12-01T03:00:00+00:0015.0NaNNoneNaNhttps://api.tvmaze.com/episodes/231511661674https://www.tvmaze.com/shows/61674/sono-koi-mousukoshi-atatamemasukaSono koi Mousukoshi AtatamemasukaScriptedJapanese[Romance]Ended15.015.02020-10-202020-12-22https://www.paravi.jp/static/koisuko22:00[Tuesday]NaN1NaN342.0ParaviJapanJPAsia/TokyoNoneNaNNaN419045.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/404/1012331.jpghttps://static.tvmaze.com/uploads/images/original_untouched/404/1012331.jpg<p>It's spin-off drama of <b>"Kono Koi Atatamemasu ka"</b></p>1650915213https://api.tvmaze.com/shows/61674https://api.tvmaze.com/episodes/2315117NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
61973538https://www.tvmaze.com/episodes/1973538/please-wait-brother-1x17-episode-17Episode 17117regular2020-12-0112:002020-12-01T04:00:00+00:0037.0NaNNoneNaNhttps://api.tvmaze.com/episodes/197353852038https://www.tvmaze.com/shows/52038/please-wait-brotherPlease Wait, BrotherScriptedChinese[Comedy]Ended37.037.02020-11-172020-12-08None12:00[Tuesday, Wednesday, Thursday]NaN21NaN104.0Tencent QQChinaCNAsia/Shanghaihttps://v.qq.com/NaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/284/711240.jpghttps://static.tvmaze.com/uploads/images/original_untouched/284/711240.jpgNone1607697965https://api.tvmaze.com/shows/52038https://api.tvmaze.com/episodes/1973545NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
71973539https://www.tvmaze.com/episodes/1973539/please-wait-brother-1x18-episode-18Episode 18118regular2020-12-0112:002020-12-01T04:00:00+00:0037.0NaNNoneNaNhttps://api.tvmaze.com/episodes/197353952038https://www.tvmaze.com/shows/52038/please-wait-brotherPlease Wait, BrotherScriptedChinese[Comedy]Ended37.037.02020-11-172020-12-08None12:00[Tuesday, Wednesday, Thursday]NaN21NaN104.0Tencent QQChinaCNAsia/Shanghaihttps://v.qq.com/NaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/284/711240.jpghttps://static.tvmaze.com/uploads/images/original_untouched/284/711240.jpgNone1607697965https://api.tvmaze.com/shows/52038https://api.tvmaze.com/episodes/1973545NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
81984264https://www.tvmaze.com/episodes/1984264/fearless-whispers-1x51-episode-51Episode 51151regular2020-12-012020-12-01T04:00:00+00:0060.0NaNNoneNaNhttps://api.tvmaze.com/episodes/198426452373https://www.tvmaze.com/shows/52373/fearless-whispersFearless WhispersScriptedChinese[Drama, Romance, History]Ended60.060.02020-11-062020-12-01None[Monday, Tuesday, Wednesday, Thursday, Friday, Saturday, Sunday]NaN15NaNNaNNaNNaNNaNNaNNaNNaNNaN391554.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/288/721078.jpghttps://static.tvmaze.com/uploads/images/original_untouched/288/721078.jpg<p>A story revolving around a fresh graduate who holds an idealistic view of what's right and wrong, yet realizes that the very institution he chose to serve falls heavily onto a gray area caught in the struggles during chaotic times.</p>1607717005https://api.tvmaze.com/shows/52373https://api.tvmaze.com/episodes/1984264NaNNaN1282.0CCTV-1ChinaCNAsia/ShanghaiNaNNaNNaNNaNNaNNaNNaNNaN
92082171https://www.tvmaze.com/episodes/2082171/ling-jian-zun-4x28-di128ji第128集428regular2020-12-012020-12-01T04:00:00+00:0010.0NaNNoneNaNhttps://api.tvmaze.com/episodes/208217155016https://www.tvmaze.com/shows/55016/ling-jian-zunLing Jian ZunAnimationChinese[Anime]Running10.010.02019-01-15Nonehttps://v.qq.com/x/cover/2w2legt0g8z26al.html[Tuesday, Friday]NaN52NaN104.0Tencent QQChinaCNAsia/Shanghaihttps://v.qq.com/NaNNaN364730.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/311/778535.jpghttps://static.tvmaze.com/uploads/images/original_untouched/311/778535.jpg<p>The strong man was attacked and returned to his youth. He became the weakest waste young lord. He will never let go of the enemy of the previous life in this life and must make up the regret of the previous life in this life! By the time the Spirit Sword is powerful, the protagonist will be supreme in the three worlds between heaven and earth! If there is someone doesn't obey him, he will kill him with the sword!</p><p><br /> </p>1653895786https://api.tvmaze.com/shows/55016https://api.tvmaze.com/episodes/2336755NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN

Last rows

idurlnameseasonnumbertypeairdateairtimeairstampruntimeimagesummaryrating.average_links.self.href_embedded.show.id_embedded.show.url_embedded.show.name_embedded.show.type_embedded.show.language_embedded.show.genres_embedded.show.status_embedded.show.runtime_embedded.show.averageRuntime_embedded.show.premiered_embedded.show.ended_embedded.show.officialSite_embedded.show.schedule.time_embedded.show.schedule.days_embedded.show.rating.average_embedded.show.weight_embedded.show.network_embedded.show.webChannel.id_embedded.show.webChannel.name_embedded.show.webChannel.country.name_embedded.show.webChannel.country.code_embedded.show.webChannel.country.timezone_embedded.show.webChannel.officialSite_embedded.show.dvdCountry_embedded.show.externals.tvrage_embedded.show.externals.thetvdb_embedded.show.externals.imdb_embedded.show.image.medium_embedded.show.image.original_embedded.show.summary_embedded.show.updated_embedded.show._links.self.href_embedded.show._links.previousepisode.hrefimage.mediumimage.original_embedded.show.network.id_embedded.show.network.name_embedded.show.network.country.name_embedded.show.network.country.code_embedded.show.network.country.timezone_embedded.show.network.officialSite_embedded.show._links.nextepisode.href_embedded.show.webChannel_embedded.show.image_embedded.show.webChannel.country_embedded.show.dvdCountry.name_embedded.show.dvdCountry.code_embedded.show.dvdCountry.timezone
891976871https://www.tvmaze.com/episodes/1976871/nfl-films-presents-2020-12-01-sights-and-sounds-of-successSights and Sounds of Success202013regular2020-12-0108:302020-12-01T13:30:00+00:0030.0NaNNoneNaNhttps://api.tvmaze.com/episodes/19768716441https://www.tvmaze.com/shows/6441/nfl-films-presentsNFL Films PresentsSportsEnglish[]Running30.030.01999-08-23Nonehttp://www.nfl.com/videos/nfl-films-presents08:30[Saturday]NaN27NaN30.0Naver TVCastKorea, Republic ofKRAsia/Seoulhttps://tv.naver.com/NaNNaN274175.0tt0211159https://static.tvmaze.com/uploads/images/medium_portrait/406/1016520.jpghttps://static.tvmaze.com/uploads/images/original_untouched/406/1016520.jpg<p><b>NFL Films Presents</b> is devoted to producing commercials, television programs, feature films, and documentaries on the National Football League, as well as other unrelated major events and awards shows. It is currently owned by the NFL and produces most of its videotaped content except its live game coverage, which is handled separately by the individual networks."</p>1662380496https://api.tvmaze.com/shows/6441https://api.tvmaze.com/episodes/2387401NaNNaN205.0NFL NetworkUnited StatesUSAmerica/New_YorkNaNNaNNaNNaNNaNNaNNaNNaN
902311017https://www.tvmaze.com/episodes/2311017/toki-wo-kakeru-bando-1x07-chahhan-saneCHAHHAN SANE17regular2020-12-0100:252020-12-01T15:25:00+00:0026.0NaN<p>After the audition, 'Yuki Ebana' was confessed to 'Seiichi Izumi'. 'Shiori Kato' and 'Hitoko Murakami' witnessed it, and Hitoko, who had been thinking about Seiichi, screamed and ran away, and Shiori chased it.<br />On the other hand, for some reason, 'Ryo' will be drunk with Seiichi's band members 'Taki Hiroto' and 'Tsubaki Aoi', and will be re-drinked at Taki and Taki's house. Taki tells Ryo that he is thinking of leaving the band and becoming a doctor. Ryo presses the taiko stamp that Taki can be compatible, but Taki is not serious. Taki notices that something is wrong with Ryo's body, but Ryo tells others to keep silent.<br />In Seiichi's confession, Yuki and Hitoko were jerky. Meanwhile, the president 'Yuichi Yanagishita' called and told that the major debut of 'Chahhan' was decided. Three people who rejoice.<br />However, when I went to the office a few days later, I found that the debut song was not the original song, but a song made by a stranger ('77'). The three are not convinced, but Yuki remembers something stuck in the lyrics of 'No. 77' ...</p>NaNhttps://api.tvmaze.com/episodes/231101761530https://www.tvmaze.com/shows/61530/toki-wo-kakeru-bandoToki wo Kakeru BandoScriptedJapanese[Comedy, Music, Science-Fiction]Ended27.026.02020-10-202020-12-22https://www.fujitv.co.jp/tokikake/00:25[Tuesday]NaN1NaN119.0FODJapanJPAsia/TokyoNoneNaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/403/1009836.jpghttps://static.tvmaze.com/uploads/images/original_untouched/403/1009836.jpg<p>A story about Ryo, a mysterious and self-proclaimed music producer from the future, producing a girl band of three girls and leading them to stardom. A comical and tempo conversational drama, and various trials to produce the youth of young people who play music with comedy touch.</p>1649705311https://api.tvmaze.com/shows/61530https://api.tvmaze.com/episodes/2311020https://static.tvmaze.com/uploads/images/medium_landscape/403/1009865.jpghttps://static.tvmaze.com/uploads/images/original_untouched/403/1009865.jpg1354.0Fuji TV TWOJapanJPAsia/TokyoNaNNaNNaNNaNNaNJapanJPAsia/Tokyo
912165005https://www.tvmaze.com/episodes/2165005/all-about-android-2020-12-01-android-ostracizationAndroid Ostracization202048regular2020-12-012020-12-01T17:00:00+00:0090.0NaNNoneNaNhttps://api.tvmaze.com/episodes/216500517633https://www.tvmaze.com/shows/17633/all-about-androidAll About AndroidNewsEnglish[]RunningNaN90.02011-03-29Nonehttps://twit.tv/shows/all-about-android[Tuesday]NaN44NaN102.0TwitUnited StatesUSAmerica/New_YorkNoneNaNNaN260436.0tt3589312https://static.tvmaze.com/uploads/images/medium_portrait/59/148354.jpghttps://static.tvmaze.com/uploads/images/original_untouched/59/148354.jpg<p><b>All About Android </b>delivers everything you want to know about Android each week -- the biggest news, freshest hardware, best apps and geekiest how-to's -- with Android enthusiasts Jason Howell, Florence Ion, Ron Richards, and a variety of special guests along the way.</p>1653765273https://api.tvmaze.com/shows/17633https://api.tvmaze.com/episodes/2335726NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
921963910https://www.tvmaze.com/episodes/1963910/a-teacher-1x06-episode-6Episode 616regular2020-12-012020-12-01T17:00:00+00:0024.0NaN<p>As Claire's world begins to crumble, an uncertain Eric is pressed to reveal intimate details of his relationship.</p>7.7https://api.tvmaze.com/episodes/196391038339https://www.tvmaze.com/shows/38339/a-teacherA TeacherScriptedEnglish[Drama]EndedNaN27.02020-11-102020-12-29https://www.hulu.com/series/a-teacher-1c871218-05b1-4c66-a22f-260b2cb9bbf9[Tuesday]5.894NaN2.0HuluUnited StatesUSAmerica/New_Yorkhttps://www.hulu.com/NaNNaN352440.0tt10680614https://static.tvmaze.com/uploads/images/medium_portrait/272/681431.jpghttps://static.tvmaze.com/uploads/images/original_untouched/272/681431.jpg<p><b>A Teacher</b> examines the complexities and consequences of an illegal relationship between a female teacher, Claire and her male high school student, Eric. Dissatisfied in their own lives, Claire and Eric discover an undeniable escape in each other, but their relationship accelerates faster than anticipated and the permanent damage becomes impossible to ignore.</p>1637344861https://api.tvmaze.com/shows/38339https://api.tvmaze.com/episodes/1968004https://static.tvmaze.com/uploads/images/medium_landscape/284/710176.jpghttps://static.tvmaze.com/uploads/images/original_untouched/284/710176.jpgNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
931977755https://www.tvmaze.com/episodes/1977755/tooning-out-the-news-1x105-inside-the-hill"Inside the Hill"1105regular2020-12-012020-12-01T17:00:00+00:007.0NaN<p>Inside The Hill breaks down Trump's voter fraud conspiracy theories, Biden's cabinet picks, and Senate candidate Kelly Loeffler's campaign ad with guest Rep. Linda Sanchez (D-CA).</p>NaNhttps://api.tvmaze.com/episodes/197775545812https://www.tvmaze.com/shows/45812/tooning-out-the-newsTooning Out the NewsAnimationEnglish[Comedy]RunningNaN13.02020-04-07Nonehttps://www.paramountplus.com/shows/tooning-out-the-news/[Monday, Tuesday, Wednesday, Thursday, Friday]NaN41NaN107.0Paramount+NaNNaNNaNhttps://www.paramountplus.com/NaNNaN375994.0tt12026652https://static.tvmaze.com/uploads/images/medium_portrait/245/614061.jpghttps://static.tvmaze.com/uploads/images/original_untouched/245/614061.jpg<p><b>Tooning Out the News</b> will provide short daily segments leading up to a weekly full episodes featuring a cast of animated characters mocking news of the day, and interviewing real-world guests and newsmakers.</p>1636747761https://api.tvmaze.com/shows/45812https://api.tvmaze.com/episodes/2215367NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
941979393https://www.tvmaze.com/episodes/1979393/i-was-a-teenage-felon-1x09-the-k2-kingpinThe K2 Kingpin19regular2020-12-012020-12-01T17:00:00+00:0060.0NaN<p>K2 is a mysterious and extremly destructive drug that 18 yr old Yazz not only abused but also trafficked, earning him 100k a week while also causing him to spiral out of control.</p>NaNhttps://api.tvmaze.com/episodes/197939350661https://www.tvmaze.com/shows/50661/i-was-a-teenage-felonI Was a Teenage FelonDocumentaryEnglish[Crime]Running60.060.02020-09-22Nonehttps://video.vice.com/en_us/show/i-was-a-teenage-felon[Monday]NaN41NaNNaNNaNNaNNaNNaNNaNNaNNaN385432.0tt10951438https://static.tvmaze.com/uploads/images/medium_portrait/371/929339.jpghttps://static.tvmaze.com/uploads/images/original_untouched/371/929339.jpg<p>Former criminals tell the true tales of their rollercoaster ride from average American kids to wildly successful outlaws.</p>1637762524https://api.tvmaze.com/shows/50661https://api.tvmaze.com/episodes/2207417https://static.tvmaze.com/uploads/images/medium_landscape/359/897951.jpghttps://static.tvmaze.com/uploads/images/original_untouched/359/897951.jpg1006.0Vice TVUnited StatesUSAmerica/New_YorkNaNNaNNaNNaNNaNNaNNaNNaN
951960028https://www.tvmaze.com/episodes/1960028/goede-tijden-slechte-tijden-31x54-aflevering-6309Aflevering 63093154regular2020-12-0120:002020-12-01T19:00:00+00:0023.0NaNNoneNaNhttps://api.tvmaze.com/episodes/19600282504https://www.tvmaze.com/shows/2504/goede-tijden-slechte-tijdenGoede Tijden, Slechte TijdenScriptedDutch[Drama, Romance]Running23.025.01990-10-01Nonehttp://gtst.nl/#!/20:00[Monday, Tuesday, Wednesday, Thursday]NaN83NaNNaNNaNNaNNaNNaNNaNNaN19056.0104271.0tt0096597https://static.tvmaze.com/uploads/images/medium_portrait/332/830481.jpghttps://static.tvmaze.com/uploads/images/original_untouched/332/830481.jpgNone1662346277https://api.tvmaze.com/shows/2504https://api.tvmaze.com/episodes/2379702https://static.tvmaze.com/uploads/images/medium_landscape/285/712958.jpghttps://static.tvmaze.com/uploads/images/original_untouched/285/712958.jpg112.0RTL4NetherlandsNLEurope/AmsterdamNaNhttps://api.tvmaze.com/episodes/2379703NaNNaNNaNNaNNaNNaN
961976929https://www.tvmaze.com/episodes/1976929/cheyenne-et-lola-1x03-les-chacalsLes chacals13regular2020-12-0120:402020-12-01T19:40:00+00:0050.0NaN<p>Cheyenne découvre qu'un policier ripou dont elle ignore l'identité est l'informateur de Yannick.</p>NaNhttps://api.tvmaze.com/episodes/197692950106https://www.tvmaze.com/shows/50106/cheyenne-et-lolaCheyenne et LolaScriptedFrench[Drama, Comedy, Crime]Running50.050.02020-11-24Nonehttps://go.ocs.fr/details/serie/PSCHEYENNEEW016825920:40[Tuesday]NaN40NaNNaNNaNNaNNaNNaNNaNNaNNaN281345.0tt10094402https://static.tvmaze.com/uploads/images/medium_portrait/285/713798.jpghttps://static.tvmaze.com/uploads/images/original_untouched/285/713798.jpg<p>Cheyenne has been out of jail for six months now, working as a cleaner on the ferries whilst dreaming about traveling to the Amazon. Lola is a beautiful Parisian woman, selfish and ruthless, who has just arrived in the north of France to move in with her lover. But when Cheyenne witnesses Lola killing her lover's wife, she knows she's going to be accused of the crime because of her criminal past.</p>1644650582https://api.tvmaze.com/shows/50106https://api.tvmaze.com/episodes/1976934https://static.tvmaze.com/uploads/images/medium_landscape/289/724603.jpghttps://static.tvmaze.com/uploads/images/original_untouched/289/724603.jpg432.0OCS MaxFranceFREurope/ParisNaNNaNNaNNaNNaNNaNNaNNaN
971976930https://www.tvmaze.com/episodes/1976930/cheyenne-et-lola-1x04-eldoradoEldorado14regular2020-12-0120:402020-12-01T19:40:00+00:0050.0NaN<p>Cheyenne se fait passer pour le bras droit de l'Anglais auprès d'un passeur nigérian.</p>NaNhttps://api.tvmaze.com/episodes/197693050106https://www.tvmaze.com/shows/50106/cheyenne-et-lolaCheyenne et LolaScriptedFrench[Drama, Comedy, Crime]Running50.050.02020-11-24Nonehttps://go.ocs.fr/details/serie/PSCHEYENNEEW016825920:40[Tuesday]NaN40NaNNaNNaNNaNNaNNaNNaNNaNNaN281345.0tt10094402https://static.tvmaze.com/uploads/images/medium_portrait/285/713798.jpghttps://static.tvmaze.com/uploads/images/original_untouched/285/713798.jpg<p>Cheyenne has been out of jail for six months now, working as a cleaner on the ferries whilst dreaming about traveling to the Amazon. Lola is a beautiful Parisian woman, selfish and ruthless, who has just arrived in the north of France to move in with her lover. But when Cheyenne witnesses Lola killing her lover's wife, she knows she's going to be accused of the crime because of her criminal past.</p>1644650582https://api.tvmaze.com/shows/50106https://api.tvmaze.com/episodes/1976934https://static.tvmaze.com/uploads/images/medium_landscape/289/724604.jpghttps://static.tvmaze.com/uploads/images/original_untouched/289/724604.jpg432.0OCS MaxFranceFREurope/ParisNaNNaNNaNNaNNaNNaNNaNNaN
981978451https://www.tvmaze.com/episodes/1978451/chicken-girls-7x13-breakfast-clubBreakfast Club713regular2020-12-0115:002020-12-01T20:00:00+00:0016.0NaN<p>In detention, the girls put aside their differences. </p>NaNhttps://api.tvmaze.com/episodes/197845132087https://www.tvmaze.com/shows/32087/chicken-girlsChicken GirlsScriptedEnglish[Drama, Music]RunningNaN14.02017-09-05Nonehttps://www.youtube.com/playlist?list=PLVewHiZp3_LPhqzbcZFmS3iuDm9HymTsy15:00[Tuesday]5.687NaN274.0BratUnited StatesUSAmerica/New_YorkNoneNaNNaN339854.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/355/888874.jpghttps://static.tvmaze.com/uploads/images/original_untouched/355/888874.jpg<p>Rhyme and her friends — known by their 'ship name, "The Chicken Girls" — have been dancing together forever. But this year, everything's changing...</p>1661790437https://api.tvmaze.com/shows/32087https://api.tvmaze.com/episodes/2270191https://static.tvmaze.com/uploads/images/medium_landscape/369/923709.jpghttps://static.tvmaze.com/uploads/images/original_untouched/369/923709.jpgNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN